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AI based systems design and development, entire pipeline from image/ video ingest, metadata ingest, processing, encoding, transmitting.
Implementation and testing of advanced computer vision algorithms.
Dataset search, preparation, annotation, training, testing, fine tuning of vision CNN models. Multimodal AI, LLMs, hardware deployment, explainability.
Detailed analysis of results. Documentation, version control, client support, upgrades.
Python Developer - AI/MLYour Responsibilities
- Develop, train, and optimize ML models using PyTorch, TensorFlow, and Keras.
- Build end-to-end LLM and RAG pipelines using LangChain and LangGraph.
- Work with LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI) and implement prompt engineering strategies.
- Utilize Hugging Face Transformers for model fine-tuning and deployment.
- Integrate embedding models for semantic search and retrieval systems.
- Work with transformer-based architectures (BERT, GPT, LLaMA, Mistral) for production use cases.
- Implement LLM evaluation frameworks (RAGAS, LangSmith) and performance optimization.
- Design and maintain Python microservices using FastAPI with REST/GraphQL APIs.
- Implement real-time communication with FastAPI WebSockets.
- Implement pgvector for embedding storage and similarity search with efficient indexing strategies.
- Integrate vector databases (pgvector, Pinecone, Weaviate, FAISS, Milvus) for retrieval pipelines.
- Containerize AI services with Docker and deploy on Kubernetes (EKS/GKE/AKS).
- Configure AWS infrastructure (EC2, S3, RDS, SageMaker, Lambda, CloudWatch) for AI/ML workloads.
- Version ML experiments using MLflow, Weights & Biases, or Neptune.
- Deploy models using serving frameworks (TorchServe, BentoML, TensorFlow Serving).
- Implement model monitoring, drift detection, and automated retraining pipelines.
- Build CI/CD pipelines for automated testing and deployment with ≥80% test coverage (pytest).
- Follow security best practices for AI systems (prompt injection prevention, data privacy, API key management).
- Participate in code reviews, tech talks, and AI learning sessions.
- Follow Agile/Scrum methodologies and Git best practices.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, AI/ML, or related field.
- 2–5 years of Python development experience (Python 3.9+) with strong AI/ML background.
- Hands-on experience with LangChain and LangGraph for building LLM-powered workflows and RAG systems.
- Deep learning experience with PyTorch or TensorFlow.
- Experience with Hugging Face Transformers and model fine-tuning.
- Proficiency with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and prompt engineering.
- Strong experience with FastAPI frameworks.
- Proficiency in PostgreSQL with pgvector extension for embedding storage and similarity search.
- Experience with vector databases (pgvector, Pinecone, Weaviate, FAISS, or Milvus).
- Experience with model versioning tools (MLflow, Weights & Biases, or Neptune).
- Hands-on with Docker, Kubernetes basics, and AWS cloud services.
- Skilled in Git workflows, automated testing (pytest), and CI/CD practices.
- Understanding of security principles for AI systems.
- Excellent communication and analytical thinking.
Nice to Have
- Experience with multiple vector databases (Pinecone, Weaviate, FAISS, Milvus).
- Knowledge of advanced LLM fine-tuning (LoRA, QLoRA, PEFT) and RLHF.
- Experience with model serving frameworks and distributed training.
- Familiarity with workflow orchestration tools (Airflow, Prefect, Dagster).
- Knowledge of quantization and model compression techniques.
- Experience with infrastructure as code (Terraform, CloudFormation).
- Familiarity with data versioning tools (DVC) and AutoML.
- Experience with Streamlit or Gradio for ML demos.
- Background in statistics, optimization, or applied mathematics.
- Contributions to AI/ML or LangChain/LangGraph open-source projects.
Artificial Intelligence Resercher (Computer vision)
Responsibility
• Work on Various SOTA Computer Vision Models, Dataset Augmentation & Dataset Generation
Techniques that help improve model accuracy & precision.
• Work on development & improvement of End-to-End Pipeline use cases running at scale.
• Programming skills with multi-threaded GPU CUDA computing and API Solutions.
• Proficient with Training of Detection, Classification & Segmentation Models with TensorFlow,
Pytorch, MX Net etc
Required Skills
• Strong development skills required in Python and C++.
• Ability to architect a solution based on given requirements and convert the business requirements into a technical computer vision problem statement.
• Ability to work in a fast-paced environment and coordinate across different parts of different projects.
• Bringing in the technical expertise around the implementation of best coding standards and
practices across the team.
• Extensive experience of working on edge devices like Jetson Nano, Raspberry Pi and other GPU powered low computational devices.
• Experience with using Docker, Nvidia Docker, Nvidia NGC containers for Computer Vision Deep
Learning
• Experience with Scalable Cloud Deployment Architecture for Video Analytics(Involving Kubernetes
and or Kafka)
• Good experience with any of one cloud technologies like AWS, Azure and Google Cloud.
• Experience in working with Model Optimisation for Nvidia Hardware (Tensors Conversion of both TensorFlow & Pytorch models.
• Proficient understanding of code versioning tools, such as Git.
• Proficient in Data Structures & Algorithms.
• Well versed in software design paradigms and good development practices.
• Experience with Scalable Cloud Deployment Architecture for Video Analytics(Involving Kubernetes
and or Kafka).
Role - Python Developer
Location - Ahmedabad
Experience - 1 - 2 Years
Employment Type - Full-Time
Role Overview:
We are looking for a Python-focused AI/ML Engineer to develop, train, and deploy machine learning models and AI-driven solutions. The ideal candidate should have strong Python skills and hands-on experience with ML frameworks.
Key Responsibilities:
- Build and optimize ML/DL models using Python.
- Develop data pipelines and perform data preprocessing.
- Deploy models using MLOps tools and cloud platforms.
- Collaborate with cross-functional teams to deliver AI solutions.
- Conduct model testing, tuning, and performance monitoring.
Required Skills:
- Strong proficiency in Python, NumPy, Pandas, Scikit-learn.
- Experience with TensorFlow or PyTorch.
- Understanding of ML algorithms and model evaluation.
- Familiarity with REST APIs and Git.
- Basic knowledge of cloud services (AWS/Azure/GCP).
Preferred Skills:
- Experience with NLP or Computer Vision.
- Knowledge of Docker, Kubernetes, and MLflow.
Key Responsibilities:
- Design AI-driven solutions for core veterinary workflows, such as patient triaging, diagnostics support, treatment plan suggestions, appointment scheduling, and client communications.
- Develop AI assistants and multi-agent systems to automate routine tasks like SOAP note summarization, clinical documentation (Medical Records), prescription and other reminders, and client follow-ups.
- Implement RAG pipelines leveraging veterinary knowledge bases, clinical case data, Case Summaries and standard care protocols.
- Integrate LLMs into practice management modules for intelligent querying, FAQ automation, and veterinary clinical knowledge support.
- develop and deploy AI services using Azure AI Services, Azure OpenAI, and integrate with Hapivet.ai
- Ensure secure, compliant, and scalable deployment of AI/ML models in line with veterinary data privacy standards and healthcare regulations.
- Collaborate with veterinarians, product managers, and software engineers to ensure AI solutions are clinically relevant, user-friendly, and impactful.
Required Skillset:
Machine Learning & Deep Learning for Healthcare
- Strong foundation in supervised/unsupervised learning, anomaly detection, and predictive analytics applicable to veterinary clinical data.
- Experience with CNNs (for imaging), RNNs/LSTMs (for sequential data like patient histories) and Transformers for natural language tasks.
- Proficiency with TensorFlow, PyTorch, and Hugging Face.
- Good to have understanding on GANs (medical imaging, data privacy-safe synthetic data, or image-based diagnostics)
LLMs & NLP for Veterinary Applications
- Deep understanding of transformer models (GPT, BERT, LLaMA) applied in medical/veterinary text summarization and knowledge extraction.
- Fine-tuning LLMs with techniques with PEFT, LoRA, QLoRA for domain-specific tasks.
- Expertise in Prompt Engineering and Chain of Thought (CoT) design for veterinary use cases.
- RAG pipeline development with veterinary case databases using Pinecone or Azure AI Search.
AI Agent Workflows & Orchestration
- Multi-agent coordination and AI workflow orchestration with LangChain, LangGraph, and Microsoft Autogen SDK.
- Experience with context management using Model Context Protocol (MCP) in clinical task flows.
Cloud AI Deployment & Engineering
- Experience with Azure AI, model serving (Triton, TensorFlow Serving, TorchServe).
- CI/CD for AI models, cloud security, and scalable API integration.
Programming & Data Engineering
- Advanced proficiency in Python, R
- working knowledge of TypeScript.
- Veterinary data processing experience—handling EMRs, patient histories, and diagnostic reports
- Data cleaning, transformation, and ensuring data quality for clinical applications.
Preferred Experience:
- AI/ML deployment in veterinary practice management systems or healthcare applications.
- Understanding of veterinary compliance, data sensitivity, and client confidentiality (e.g., pet health records, veterinary licensing).
- Exposure to veterinary-specific AI applications, such as diagnostic imaging analysis, clinical decision support systems, or client interaction bots.
- Familiarity with DeepSpeed, Megatron-LM, and scaling techniques for LLMs.
Soft Skills & Domain Understanding:
- “Passion for improving pet care and veterinary services through technology”.
- Strong communication skills for collaborating with veterinary professionals.
- Ability to translate clinical workflows into AI-enabled solutions.
About Synorus
Synorus is building a next-generation ecosystem of AI-first products. Our flagship legal-AI platform LexVault is redefining legal research, drafting, knowledge retrieval, and case intelligence using domain-tuned LLMs, private RAG pipelines, and secure reasoning systems.
If you are passionate about AI, legaltech, and training high-performance models — this internship will put you on the front line of innovation.
Role Overview
We are seeking passionate AI/LLM Engineering Interns who can:
- Fine-tune LLMs for legal domain use-cases
- Train and experiment with open-source foundation models
- Work with large datasets efficiently
- Build RAG pipelines and text-processing frameworks
- Run model training workflows on Google Colab / Kaggle / Cloud GPUs
This is a hands-on engineering and research internship — you will work directly with senior founders & technical leadership.
Key Responsibilities
- Fine-tune transformer-based models (Llama, Mistral, Gemma, etc.)
- Build and preprocess legal datasets at scale
- Develop efficient inference & training pipelines
- Evaluate models for accuracy, hallucinations, and trustworthiness
- Implement RAG architectures (vector DBs + embeddings)
- Work with GPU environments (Colab/Kaggle/Cloud)
- Contribute to model improvements, prompt engineering & safety tuning
Must-Have Skills
- Strong knowledge of Python & PyTorch
- Understanding of LLMs, Transformers, Tokenization
- Hands-on experience with HuggingFace Transformers
- Familiarity with LoRA/QLoRA, PEFT training
- Data wrangling: Pandas, NumPy, tokenizers
- Ability to handle multi-GB datasets efficiently
Bonus Skills
(Not mandatory — but a strong plus)
- Experience with RAG / vector DBs (Chroma, Qdrant, LanceDB)
- Familiarity with vLLM, llama.cpp, GGUF
- Worked on summarization, Q&A or document-AI projects
- Knowledge of legal texts (Indian laws/case-law/statutes)
- Open-source contributions or research work
What You Will Gain
- Real-world training on LLM fine-tuning & legal AI
- Exposure to production-grade AI pipelines
- Direct mentorship from engineering leadership
- Research + industry project portfolio
- Letter of experience + potential full-time offer
Ideal Candidate
- You experiment with models on weekends
- You love pushing GPUs to their limits
- You prefer research + implementation over theory alone
- You want to build AI that matters — not just demos
Location - Remote
Stipend - 5K - 10K
Job Title: AI Engineer
Location: Bengaluru
Experience: 3 Years
Working Days: 5 Days
About the Role
We’re reimagining how enterprises interact with documents and workflows—starting with BFSI and healthcare. Our AI-first platforms are transforming credit decisioning, document intelligence, and underwriting at scale. The focus is on Intelligent Document Processing (IDP), GenAI-powered analysis, and human-in-the-loop (HITL) automation to accelerate outcomes across lending, insurance, and compliance workflows.
As an AI Engineer, you’ll be part of a high-caliber engineering team building next-gen AI systems that:
- Power robust APIs and platforms used by underwriters, credit analysts, and financial institutions.
- Build and integrate GenAI agents.
- Enable “human-in-the-loop” workflows for high-assurance decisions in real-world conditions.
Key Responsibilities
- Build and optimize ML/DL models for document understanding, classification, and summarization.
- Apply LLMs and RAG techniques for validation, search, and question-answering tasks.
- Design and maintain data pipelines for structured and unstructured inputs (PDFs, OCR text, JSON, etc.).
- Package and deploy models as REST APIs or microservices in production environments.
- Collaborate with engineering teams to integrate models into existing products and workflows.
- Continuously monitor and retrain models to ensure reliability and performance.
- Stay updated on emerging AI frameworks, architectures, and open-source tools; propose improvements to internal systems.
Required Skills & Experience
- 2–5 years of hands-on experience in AI/ML model development, fine-tuning, and building ML solutions.
- Strong Python proficiency with libraries such as NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow.
- Solid understanding of transformers, embeddings, and NLP pipelines.
- Experience working with LLMs (OpenAI, Claude, Gemini, etc.) and frameworks like LangChain.
- Exposure to OCR, document parsing, and unstructured text analytics.
- Familiarity with model serving, APIs, and microservice architectures (FastAPI, Flask).
- Working knowledge of Docker, cloud environments (AWS/GCP/Azure), and CI/CD pipelines.
- Strong grasp of data preprocessing, evaluation metrics, and model validation workflows.
- Excellent problem-solving ability, structured thinking, and clean, production-ready coding practices.
About the Role
We are looking for a passionate AI Engineer Intern (B.Tech, M.Tech / M.S. or equivalent) with strong foundations in Artificial Intelligence, Computer Vision, and Deep Learning to join our R&D team.
You will help us build and train realistic face-swap and deepfake video models, powering the next generation of AI-driven video synthesis technology.
This is a remote, individual-contributor role offering exposure to cutting-edge AI model development in a startup-like environment.
Key Responsibilities
- Research, implement, and fine-tune face-swap / deepfake architectures (e.g., FaceSwap, SimSwap, DeepFaceLab, LatentSync, Wav2Lip).
- Train and optimize models for realistic facial reenactment and temporal consistency.
- Work with GANs, VAEs, and diffusion models for video synthesis.
- Handle dataset creation, cleaning, and augmentation for face-video tasks.
- Collaborate with the AI core team to deploy trained models in production environments.
- Maintain clean, modular, and reproducible pipelines using Git and experiment-tracking tools.
Required Qualifications
- B.Tech, M.Tech / M.S. (or equivalent) in AI / ML / Computer Vision / Deep Learning.
- Certifications in AI or Deep Learning (DeepLearning.AI, NVIDIA DLI, Coursera, etc.).
- Proficiency in PyTorch or TensorFlow, OpenCV, FFmpeg.
- Understanding of CNNs, Autoencoders, GANs, Diffusion Models.
- Familiarity with datasets like CelebA, VoxCeleb, FFHQ, DFDC, etc.
- Good grasp of data preprocessing, model evaluation, and performance tuning.
Preferred Skills
- Prior hands-on experience with face-swap or lip-sync frameworks.
- Exposure to 3D morphable models, NeRF, motion transfer, or facial landmark tracking.
- Knowledge of multi-GPU training and model optimization.
- Familiarity with Rust / Python backend integration for inference pipelines.
What We Offer
- Work directly on production-grade AI video synthesis systems.
- Remote-first, flexible working hours.
- Mentorship from senior AI researchers and engineers.
- Opportunity to transition into a full-time role upon outstanding performance.
Location: Remote | Stipend: ₹10,000/month | Duration: 3–6 months
MLOps | Exp- 10 + yrs
Working Shift Hour - Anytime in between 11 am to 11pm. ( It can start from 11am, 12am , 1pm or 2 pm)
Location- Remote ( C2C Oppurtunity)
Required Skills:
- Expertise in deploying Tensorflow and PyTorch. Experience with both computer vision and language models strongly preferred.
- The ability to select and transform features at scale for BERT-based models.
- Setting up monitoring and evaluation metrics in Sagemaker.
- Creating A/B tests for ML models in Sagemaker.
- Expertise in model deployment and orchestration.
Experience:
- Deploying transformer-based models with Tensorflow or PyTorch in production workflows.
- Resource selection, evaluation and optimization for production model deployments.
- Familiarity and demonstrated experience with the following strongly preferred:
- Convolutional neural networks
- Feedforwards Neural networks
- Diffusion Models
- Ranking Algorithms
- Approximate Nearest Neighbors - HNSW.
- Bayesian Methods
- Regression Models
- Decision Trees
- Clustering (K-Means, DBScan).
Job Summary:
We are seeking a skilled and forward-thinking Cloud AI Professional to join our technology team. The ideal candidate will have expertise in designing, deploying, and managing artificial intelligence and machine learning solutions in cloud environments (AWS, Azure, or Google Cloud). You will work at the intersection of cloud computing and AI, helping to build scalable, secure, and high-performance AI-driven applications and services.
Key Responsibilities:
- Design, develop, and deploy AI/ML models in cloud environments (AWS, GCP, Azure).
- Build and manage end-to-end ML pipelines using cloud-native tools (e.g., SageMaker, Vertex AI, Azure ML).
- Collaborate with data scientists, engineers, and stakeholders to define AI use cases and deliver solutions.
- Automate model training, testing, and deployment using MLOps practices.
- Optimize performance and cost of AI/ML workloads in the cloud.
- Ensure security, compliance, and scalability of deployed AI services.
- Monitor model performance in production and retrain models as needed.
- Stay current with new developments in AI/ML and cloud technologies.
Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 3+ years of experience in AI/ML and cloud computing.
- Hands-on experience with cloud platforms (AWS, GCP, or Azure).
- Proficient in Python, TensorFlow, PyTorch, or similar frameworks.
- Strong understanding of MLOps tools and CI/CD for machine learning.
- Experience with containerization (Docker, Kubernetes).
- Familiarity with cloud-native data services (e.g., BigQuery, S3, Cosmos DB).
Preferred Qualifications:
- Certifications in Cloud (e.g., AWS Certified Machine Learning, Google Cloud Professional ML Engineer).
- Experience with generative AI, LLMs, or real-time inferencing.
- Knowledge of data governance and ethical AI practices.
- Experience with REST APIs and microservices architecture.
Soft Skills:
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration abilities.
- Ability to work in a fast-paced, agile environment.
We’re seeking a highly skilled, execution-focused Senior Data Scientist with a minimum of 5 years of experience. This role demands hands-on expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving data-driven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problem-solving ability, and ownership in delivering business impact through data science.
Responsibilities
- Design, build, and deploy scalable machine learning models into production systems.
- Develop advanced analytics and predictive models using Python, SQL, and popular ML/DL frameworks (Pandas, Scikit-learn, TensorFlow, PyTorch).
- Leverage Databricks, Apache Spark, and Hadoop for large-scale data processing and model training.
- Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration.
- Collaborate with engineering teams to integrate models into cloud-based applications on AWS.
- Optimize query performance, storage usage, and data pipelines for efficiency.
- Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment.
- Drive initiatives independently with high ownership and accountability.
- Stay up to date with industry best practices in machine learning, big data, and cloud-native deployments.
Requirements:
- Minimum 5 years of experience in Data Science or Applied Machine Learning.
- Strong proficiency in Python, SQL, and ML libraries (Pandas, Scikit-learn, TensorFlow, PyTorch).
- Proven expertise in deploying ML models into production systems.
- Experience with big data platforms (Hadoop, Spark) and distributed data processing.
- Hands-on experience with Databricks, Airflow, and AWS EMR.
- Strong knowledge of AWS cloud services (S3, Lambda, SageMaker, EC2, etc.).
- Solid understanding of query optimization, storage systems, and data pipelines.
- Excellent problem-solving skills, with the ability to design scalable solutions.
- Strong communication and collaboration skills to work in cross-functional teams.
Benefits:
- Best in class salary: We hire only the best, and we pay accordingly.
- Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field.
- Keep on learning with a world-class team: Work with the best in the field, challenge yourself constantly, and learn something new every day.
About Us:
Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world! We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore. Since 2019, Proximity has created and grown high-impact, scalable products used by 370 million daily users, with a total net worth of $45.7 billion among our client companies.
Today, we are a global team of coders, designers, product managers, geeks, and experts. We solve complex problems and build cutting-edge tech, at scale. Our team of Proxonauts is growing quickly, which means your impact on the company’s success will be huge. You’ll have the chance to work with experienced leaders who have built and led multiple tech, product, and design teams.
Job Details
- Job Title: Lead II - Software Engineering- AI, NLP, Python, Data science
- Industry: Technology
- Domain - Information technology (IT)
- Experience Required: 7-9 years
- Employment Type: Full Time
- Job Location: Bangalore
- CTC Range: Best in Industry
Job Description:
Role Proficiency:
Act creatively to develop applications by selecting appropriate technical options optimizing application development maintenance and performance by employing design patterns and reusing proven solutions. Account for others' developmental activities; assisting Project Manager in day-to-day project execution.
Additional Comments:
Mandatory Skills Data Science Skill to Evaluate AI, Gen AI, RAG, Data Science
Experience 8 to 10 Years
Location Bengaluru
Job Description
Job Title AI Engineer Mandatory Skills Artificial Intelligence, Natural Language Processing, python, data science Position AI Engineer – LLM & RAG Specialization Company Name: Sony India Software Centre About the role: We are seeking a highly skilled AI Engineer with 8-10 years of experience to join our innovation-driven team. This role focuses on the design, development, and deployment of advanced enterprise-scale Large Language Models (eLLM) and Retrieval Augmented Generation (RAG) solutions. You will work on end-to-end AI pipelines, from data processing to cloud deployment, delivering impactful solutions that enhance Sony’s products and services. Key Responsibilities: Design, implement, and optimize LLM-powered applications, ensuring high performance and scalability for enterprise use cases. Develop and maintain RAG pipelines, including vector database integration (e.g., Pinecone, Weaviate, FAISS) and embedding model optimization. Deploy, monitor, and maintain AI/ML models in production, ensuring reliability, security, and compliance. Collaborate with product, research, and engineering teams to integrate AI solutions into existing applications and workflows. Research and evaluate the latest LLM and AI advancements, recommending tools and architectures for continuous improvement. Preprocess, clean, and engineer features from large datasets to improve model accuracy and efficiency. Conduct code reviews and enforce AI/ML engineering best practices. Document architecture, pipelines, and results; present findings to both technical and business stakeholders. Job Description: 8-10 years of professional experience in AI/ML engineering, with at least 4+ years in LLM development and deployment. Proven expertise in RAG architectures, vector databases, and embedding models. Strong proficiency in Python; familiarity with Java, R, or other relevant languages is a plus. Experience with AI/ML frameworks (PyTorch, TensorFlow, etc.) and relevant deployment tools. Hands-on experience with cloud-based AI platforms such as AWS SageMaker, AWS Q Business, AWS Bedrock or Azure Machine Learning. Experience in designing, developing, and deploying Agentic AI systems, with a focus on creating autonomous agents that can reason, plan, and execute tasks to achieve specific goals. Understanding of security concepts in AI systems, including vulnerabilities and mitigation strategies. Solid knowledge of data processing, feature engineering, and working with large-scale datasets. Experience in designing and implementing AI-native applications and agentic workflows using the Model Context Protocol (MCP) is nice to have. Strong problem-solving skills, analytical thinking, and attention to detail. Excellent communication skills with the ability to explain complex AI concepts to diverse audiences. Day-to-day responsibilities: Design and deploy AI-driven solutions to address specific security challenges, such as threat detection, vulnerability prioritization, and security automation. Optimize LLM-based models for various security use cases, including chatbot development for security awareness or automated incident response. Implement and manage RAG pipelines for enhanced LLM performance. Integrate AI models with existing security tools, including Endpoint Detection and Response (EDR), Threat and Vulnerability Management (TVM) platforms, and Data Science/Analytics platforms. This will involve working with APIs and understanding data flows. Develop and implement metrics to evaluate the performance of AI models. Monitor deployed models for accuracy and performance and retrain as needed. Adhere to security best practices and ensure that all AI solutions are developed and deployed securely. Consider data privacy and compliance requirements. Work closely with other team members to understand security requirements and translate them into AI-driven solutions. Communicate effectively with stakeholders, including senior management, to present project updates and findings. Stay up to date with the latest advancements in AI/ML and security and identify opportunities to leverage new technologies to improve our security posture. Maintain thorough documentation of AI models, code, and processes. What We Offer Opportunity to work on cutting-edge LLM and RAG projects with global impact. A collaborative environment fostering innovation, research, and skill growth. Competitive salary, comprehensive benefits, and flexible work arrangements. The chance to shape AI-powered features in Sony’s next-generation products. Be able to function in an environment where the team is virtual and geographically dispersed
Education Qualification: Graduate
Skills: AI, NLP, Python, Data science
Must-Haves
Skills
AI, NLP, Python, Data science
NP: Immediate – 30 Days
🎯 Ideal Candidate Profile:
This role requires a seasoned engineer/scientist with a strong academic background from a premier institution and significant hands-on experience in deep learning (specifically image processing) within a hardware or product manufacturing environment.
📋 Must-Have Requirements:
Experience & Education Combinations:
Candidates must meet one of the following criteria:
- Doctorate (PhD) + 2 years of related work experience
- Master's Degree + 5 years of related work experience
- Bachelor's Degree + 7 years of related work experience
Technical Skills:
- Minimum 5 years of hands-on experience in all of the following:
- Python
- Deep Learning (DL)
- Machine Learning (ML)
- Algorithm Development
- Image Processing
- 3.5 to 4 years of strong proficiency with PyTorch OR TensorFlow / Keras.
Industry & Institute:
- Education: Must be from a premier institute (IIT, IISC, IIIT, NIT, BITS) or a recognized regional tier 1 college.
- Industry: Current or past experience in a Product, Semiconductor, or Hardware Manufacturing company is mandatory.
- Preference: Candidates from engineering product companies are strongly preferred.
ℹ️ Additional Role Details:
- Interview Process: 3 technical rounds followed by 1 HR round.
- Work Model: Hybrid (requiring 3 days per week in the office).
Based on the job description you provided, here is a detailed breakdown of the Required Skills and Qualifications for this AI/ML/LLM role, formatted for clarity.
📝 Required Skills and Competencies:
💻 Programming & ML Prototyping:
- Strong Proficiency: Python, Data Structures, and Algorithms.
- Hands-on Experience: NumPy, Pandas, Scikit-learn (for ML prototyping).
🤖 Machine Learning Frameworks:
- Core Concepts: Solid understanding of:
- Supervised/Unsupervised Learning
- Regularization
- Feature Engineering
- Model Selection
- Cross-Validation
- Ensemble Methods: Experience with models like XGBoost and LightGBM.
🧠 Deep Learning Techniques:
- Frameworks: Proficiency with PyTorch OR TensorFlow / Keras.
- Architectures: Knowledge of:
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Long Short-Term Memory networks (LSTMs)
- Transformers
- Attention Mechanisms
- Optimization: Familiarity with optimization techniques (e.g., Adam, SGD), Dropout, and Batch Normalization.
💬 LLMs & RAG (Retrieval-Augmented Generation):
- Hugging Face: Experience with the Transformers library (tokenizers, embeddings, model fine-tuning).
- Vector Databases: Familiarity with Milvus, FAISS, Pinecone, or ElasticSearch.
- Advanced Techniques: Proficiency in:
- Prompt Engineering
- Function/Tool Calling
- JSON Schema Outputs
🛠️ Data & Tools:
- Data Management: SQL fundamentals; exposure to data wrangling and pipelines.
- Tools: Experience with Git/GitHub, Jupyter, and basic Docker.
🎓 Minimum Qualifications (Experience & Education Combinations):
Candidates must have experience building AI systems/solutions with Machine Learning, Deep Learning, and LLMs, meeting one of the following criteria:
- Doctorate (Academic) Degree + 2 years of related work experience.
- Master's Level Degree + 5 years of related work experience.
- Bachelor's Level Degree + 7 years of related work experience.
⭐ Preferred Traits and Mindset:
- Academic Foundation: Solid academic background with strong applied ML/DL exposure.
- Curiosity: Eagerness to learn cutting-edge AI and willingness to experiment.
- Communication: Clear communicator who can explain ML/LLM trade-offs simply.
- Ownership: Strong problem-solving and ownership mindset.
Job Title: AI / Machine Learning Engineer
Company: Apprication Pvt Ltd
Location: Goregaon East
Employment Type: Full-time
Experience: 2.5-4 Years
- Bachelor’s or Master’s in Computer Science, Machine Learning, Data Science, or related field.
- Proven experience of 2.5-4 years as an AI/ML Engineer, Data Scientist, or AI Application Developer.
- Strong programming skills in Python (TensorFlow, PyTorch, Scikit-learn); familiarity with LangChain, Hugging Face, OpenAI API is a plus.
- Experience in model deployment, serving, and optimization (FastAPI, Flask, Django, or Node.js).
- Proficiency with databases (SQL and NoSQL: MySQL, PostgreSQL, MongoDB).
- Hands-on experience with cloud ML services (Sage Maker, Vertex AI, Azure ML) and DevOps tools (Docker, Kubernetes, CI/CD).
- Knowledge of MLOps practices: model versioning, monitoring, retraining, experiment tracking.
- Familiarity with frontend frameworks (React.js, Angular, Vue.js) for building AI-driven interfaces (nice to have).
- Strong understanding of data structures, algorithms, APIs, and distributed systems.
- Excellent problem-solving, analytical, and communication skills.
- Develop and maintain ETL pipelines, data preprocessing workflows, and feature engineering processes.
- Ensure solutions meet security, compliance, and performance standards.
- Stay updated with the latest research and trends in deep learning, generative AI, and LLMs.
About ThoughtClan Technologies
ThoughtClan is a niche, technology-focused, 100+ people strong software company that works on building complex enterprise-scale web and mobile-oriented digitalization and data science-related projects. They are in IT Services as well as Product Development space. They focus on applying technology to enable businesses to function better. ThoughtClan is a team of highly specialized technical folks and is growing rapidly.
They have expertise in developing projects related to:
- Data Science — including Image Analytics, Video Analytics, Building AI/ML-based Prediction Models, etc.
- Blockchain — based Cryptocurrency and NFT projects.
- Enterprise-Scale Greenfield Web and Mobile Application Development, Integration, eCommerce, Marketing, and Content Management projects.
We are looking for a Data Scientist to join our fast-growing team.
The candidate must have:
- 3–4 years’ experience in Data Modeling in Python and AI/ML.
- Hands-on experience with Machine Learning and Deep Learning techniques and tools. Tools: RAG, LLMs, Agentic AI, Langchain, Langgraph, PyTorch, OpenCV, Pandas, Scikit Learn, CrewAI, Autogen or AI chatbots. Proven ability to use/create algorithms and run simulations. Experience: Minimum 1–1.5 years or 2 projects. A technical understanding of Microservice Architectures is a plus.
- Good knowledge of Azure Platform for deployment.
- Good knowledge of web frameworks such as Flask.
- Hands-on knowledge on a NoSQL database (Maria DB, Mongo DB, etc.).
- Experience in Visualization of Data using tools like D3.js, Plotly, Power BI, and Tableau. Experience in visualizing large data is a plus.
- Experience using a variety of data mining/data analysis methods with the ability to drive business results using data-based insights and work with large data sets.
- Comfortable working with a wide range of stakeholders and functional teams.
- Good designing skills and communication skills.
- Good knowledge of front-end technologies (HTML, CSS, etc.) would be an advantage.
Exp: 4 to 8 Years
CTC: up to 40 LPA
Mandatory Criteria
- 5–7 years of hands-on experience in building and deploying AI solutions, ideally in fintech or financial services.
- Strong coding skills in Python and familiarity with libraries like TensorFlow, PyTorch, scikit-learn, XGBoost, etc.
- Experience with NLP, time series forecasting, anomaly detection, or graph ML relevant to fintech applications.
- Solid understanding of MLOps concepts – model versioning, deployment, monitoring.
- Experience working with cloud platforms (AWS/GCP/Azure) and ML services (e.g., SageMaker, Vertex AI).
- Familiarity with Docker, Kubernetes, or other containerization tools for model deployment is a plus.
- Comfortable working with large-scale structured and unstructured datasets. Experience with LLMs or generative AI for fintech-specific use cases.
- Exposure to RegTech, risk modeling, or algorithmic trading.
- Publications, GitHub contributions, or Kaggle competitions.
- Familiarity with SQL/NoSQL databases and data pipelines (e.g., Airflow, Spark, etc.).
If interested kindly share your updated resume on 82008 31681
Job Title: Senior AI/ML/DL Engineer
Location: Hyderabad
Department: Artificial Intelligence/Machine Learning
Job Summary:
We are seeking a highly skilled and motivated Senior AI/ML/DL Engineer to contribute to
the development and implementation of advanced artificial intelligence, machine learning,
and deep learning solutions. The ideal candidate will have a strong technical background in
AI/ML/DL, hands-on experience in building scalable models, and a passion for solving
complex problems using data-driven approaches. This role involves working closely with
cross-functional teams to deliver innovative AI/ML solutions aligned with business objectives.
Key Responsibilities:
Technical Execution:
● Design, develop, and deploy AI/ML/DL models and algorithms to solve business
challenges.
● Stay up-to-date with the latest advancements in AI/ML/DL technologies and integrate
them into solutions.
● Implement best practices for model development, validation, and deployment.
Project Development:
● Collaborate with stakeholders to identify business opportunities and translate them
into AI/ML projects.
● Work on the end-to-end lifecycle of AI/ML projects, including data collection,
preprocessing, model training, evaluation, and deployment.
● Ensure the scalability, reliability, and performance of AI/ML solutions in production
environments.
Cross-Functional Collaboration:
● Work closely with product managers, software engineers, and domain experts to
integrate AI/ML capabilities into products and services.
● Communicate complex technical concepts to non-technical stakeholders effectively.
Research and Innovation:●
Explore new AI/ML techniques and methodologies to enhance solution capabilities.
● Prototype and experiment with novel approaches to solve challenging problems.
●Contribute to internal knowledge-sharing initiatives and documentation.
Quality Assurance & MLOps:
● Ensure the accuracy, robustness, and ethical use of AI/ML models.
● Implement monitoring and maintenance processes for deployed models to ensure long-term performance.
● Follow MLOps practices for efficient deployment and monitoring of AI/ML solutions.
Qualifications:
Education:
● Bachelors/Master’s or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
Experience:
● 5+ years of experience in AI/ML/DL, with a proven track record of delivering AI/ML solutions in production environments.
● Strong experience with programming languages such as Python, R, or Java.
● Proficiency in AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-learn,Keras).
● Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies
(e.g., Hadoop, Spark).
● Familiarity with MLOps practices and tools for model deployment and monitoring.
Skills:
● Strong understanding of machine learning algorithms, deep learning architectures,
and statistical modeling.
● Excellent problem-solving and analytical skills.
● Strong communication and interpersonal skills.
● Ability to manage multiple projects and prioritize effectively.
Preferred Qualifications:
● Experience in natural language processing (NLP), computer vision, or reinforcement
learning.
● Knowledge of ethical AI practices and regulatory compliance.
● Publications or contributions to the AI/ML community (e.g., research papers,open-source projects).
What We Offer:
● Competitive salary and benefits package.
● Opportunities for professional development and career growth.
● A collaborative and innovative work environment.
● The chance to work on impactful projects that leverage cutting-edge AI/ML technologies.
Role: Data Scientist (Python + R Expertise)
Exp: 8 -12 Years
CTC: up to 30 LPA
Required Skills & Qualifications:
- 8–12 years of hands-on experience as a Data Scientist or in a similar analytical role.
- Strong expertise in Python and R for data analysis, modeling, and visualization.
- Proficiency in machine learning frameworks (scikit-learn, TensorFlow, PyTorch, caret, etc.).
- Strong understanding of statistical modeling, hypothesis testing, regression, and classification techniques.
- Experience with SQL and working with large-scale structured and unstructured data.
- Familiarity with cloud platforms (AWS, Azure, or GCP) and deployment practices (Docker, MLflow).
- Excellent analytical, problem-solving, and communication skills.
Preferred Skills:
- Experience with NLP, time series forecasting, or deep learning projects.
- Exposure to data visualization tools (Tableau, Power BI, or R Shiny).
- Experience working in product or data-driven organizations.
- Knowledge of MLOps and model lifecycle management is a plus.
If interested kindly share your updated resume on 82008 31681
JOB DESCRIPTION/PREFERRED QUALIFICATIONS:
REQUIRED SKILLS/COMPETENCIES:
Programming Languages:
- Strong in Python, data structures, and algorithms.
- Hands-on with NumPy, Pandas, Scikit-learn for ML prototyping.
Machine Learning Frameworks:
- Understanding of supervised/unsupervised learning, regularization, feature engineering, model selection, cross-validation, ensemble methods (XGBoost, LightGBM).
Deep Learning Techniques:
- Proficiency with PyTorch or TensorFlow/Keras
- Knowledge of CNNs, RNNs, LSTMs, Transformers, Attention mechanisms.
- Familiarity with optimization (Adam, SGD), dropout, batch norm.
LLMs & RAG:
- Hugging Face Transformers (tokenizers, embeddings, model fine-tuning).
- Vector databases (Milvus, FAISS, Pinecone, ElasticSearch).
- Prompt engineering, function/tool calling, JSON schema outputs.
Data & Tools:
- SQL fundamentals; exposure to data wrangling and pipelines.
- Git/GitHub, Jupyter, basic Docker.
WHAT ARE WE LOOKING FOR?
- Solid academic foundation with strong applied ML/DL exposure.
- Curiosity to learn cutting-edge AI and willingness to experiment.
- Clear communicator who can explain ML/LLM trade-offs simply.
- Strong problem-solving and ownership mindset.
MINIMUM QUALIFICATIONS:
- Doctorate (Academic) Degree and 2 years related work experience; Master's Level Degree and related work experience of 5 years; Bachelor's Level Degree and related work experience of 7 years in building AI systems/solutions with Machine Learning, Deep Learning, and LLMs.
MUST-HAVES:
- Education/qualification: Preferably from premier Institute like IIT, IISC, IIIT, NIT and BITS. Also regional tier 1 colleges.
- Doctorate (Academic) Degree and 2 years related work experience; or Master's Level Degree and related work experience of 5 years; or Bachelor's Level Degree and related work experience of 7 years
- Min 5 yrs experience in the Mandatory Skills: Python, Deep Learning, Machine Learning, Algorithm Development and Image Processing
- 3.5 to 4 yrs proficiency with PyTorch or TensorFlow/Keras
- Candidates from engineering product companies have higher chances of getting shortlisted (current company or past experience)
QUESTIONNAIRE:
Do you have at least 5 years of experience with Python, Deep Learning, Machine Learning, Algorithm Development, and Image Processing? Please mention the skills and years of experience:
Do you have experience with PyTorch or TensorFlow / Keras?
- PyTorch
- TensorFlow / Keras
- Both
How many years of experience do you have with PyTorch or TensorFlow / Keras?
- Less than 3 years
- 3 to 3.5 years
- 3.5 to 4 years
- More than 4 years
Is the candidate willing to relocate to Chennai?
- Ready to relocate
- Based in Chennai
What type of company have you worked for in your career?
- Service-based IT company
- Product company
- Semiconductor company
- Hardware manufacturing company
- None of the above
Role: Sr. Data Scientist
Exp: 4 -8 Years
CTC: up to 28 LPA
Technical Skills:
o Strong programming skills in Python, with hands-on experience in deep learning frameworks like TensorFlow, PyTorch, or Keras.
o Familiarity with Databricks notebooks, MLflow, and Delta Lake for scalable machine learning workflows.
o Experience with MLOps best practices, including model versioning, CI/CD pipelines, and automated deployment.
o Proficiency in data preprocessing, augmentation, and handling large-scale image/video datasets.
o Solid understanding of computer vision algorithms, including CNNs, transfer learning, and transformer-based vision models (e.g., ViT).
o Exposure to natural language processing (NLP) techniques is a plus.
Cloud & Infrastructure:
o Strong expertise in Azure cloud ecosystem,
o Experience working in UNIX/Linux environments and using command-line tools for automation and scripting.
If interested kindly share your updated resume at 82008 31681
Role: Sr. Data Scientist
Exp: 4-8 Years
CTC: up to 25 LPA
Technical Skills:
● Strong programming skills in Python, with hands-on experience in deep learning frameworks like TensorFlow, PyTorch, or Keras.
● Familiarity with Databricks notebooks, MLflow, and Delta Lake for scalable machine learning workflows.
● Experience with MLOps best practices, including model versioning, CI/CD pipelines, and automated deployment.
● Proficiency in data preprocessing, augmentation, and handling large-scale image/video datasets.
● Solid understanding of computer vision algorithms, including CNNs, transfer learning, and transformer-based vision models (e.g., ViT).
● Exposure to natural language processing (NLP) techniques is a plus.
• Educational Qualifications:
- B.E./B.Tech/M.Tech/MCA in Computer Science, Electronics & Communication, Electrical Engineering, or a related field.
- A master’s degree in computer science, Artificial Intelligence, or a specialization in Deep Learning or Computer Vision is highly preferred
If interested share your resume on 82008 31681
Role: Sr. Data Scientist
Exp: 4-8 Years
CTC: up to 25 LPA
Technical Skills:
● Strong programming skills in Python, with hands-on experience in deep learning frameworks like TensorFlow, PyTorch, or Keras.
● Familiarity with Databricks notebooks, MLflow, and Delta Lake for scalable machine learning workflows.
● Experience with MLOps best practices, including model versioning, CI/CD pipelines, and automated deployment.
● Proficiency in data preprocessing, augmentation, and handling large-scale image/video datasets.
● Solid understanding of computer vision algorithms, including CNNs, transfer learning, and transformer-based vision models (e.g., ViT).
● Exposure to natural language processing (NLP) techniques is a plus.
• Educational Qualifications:
- B.E./B.Tech/M.Tech/MCA in Computer Science, Electronics & Communication, Electrical Engineering, or a related field.
- A master’s degree in computer science, Artificial Intelligence, or a specialization in Deep Learning or Computer Vision is highly preferred
JOB DESCRIPTION/PREFERRED QUALIFICATIONS:
KEY RESPONSIBILITIES:
- Lead and mentor a team of algorithm engineers, providing guidance and support to ensure their professional growth and success.
- Develop and maintain the infrastructure required for the deployment and execution of algorithms at scale.
- Collaborate with data scientists, software engineers, and product managers to design and implement robust and scalable algorithmic solutions.
- Optimize algorithm performance and resource utilization to meet business objectives.
- Stay up to date with the latest advancements in algorithm engineering and infrastructure technologies and apply them to improve our systems.
- Drive continuous improvement in development processes, tools, and methodologies.
QUALIFICATIONS:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Proven experience in developing computer vision and image processing algorithms and ML/DL algorithms.
- Familiar with high performance computing, parallel programming and distributed systems.
- Strong leadership and team management skills, with a track record of successfully leading engineering teams.
- Proficiency in programming languages such as Python, C++ and CUDA.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
PREFERRED QUALIFICATIONS:
- Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with GPU architecture and algo development toolkits like Docker, Apptainer.
MINIMUM QUALIFICATIONS:
- Bachelor's degree plus 8 + years of experience
- Master's degree plus 8 + years of experience
- Familiar with high performance computing, parallel programming and distributed systems.
MUST-HAVE SKILLS:
- Phd with 6 yrs industry exp or M.Tech + 8 yrs experience or B.Tech + 10 yrs experience.
- 14 yrs exp if an IC role.
- Minimum 1 yrs experience working as a Manager/Lead
- 8 years' experience in any of the programming languages such as Python/C++/CUDA.
- 8 years' experience in Machine learning, Artificial intelligence, Deep learning.
- 2 to 3 years exp in Image processing & Computer vision is a MUST
- Product / Semi-conductor / Hardware Manufacturing company experience is a MUST. Candidates should be from engineering product companies
- Candidates from Tier 1 colleges like (IIT, IIIT, VIT, NIT) (Preferred)
- Relocation to Chennai is mandatory
NICE TO HAVE SKILLS:
- Candidates from Semicon or manufacturing companies
- Candidates with more than 8 CPGA
Job Title: AI / Machine Learning Engineer
Company: Apprication Pvt Ltd
Location: Goregaon East
Employment Type: Full-time
Experience: 2.5-4 Years
About the Role
We’re seeking a highly motivated AI / Machine Learning Engineer to join our growing engineering team. You will design, build, and deploy AI-powered solutions for web and application platforms, bringing cutting-edge machine learning research into real-world production systems.
This role blends applied machine learning, backend engineering, and cloud deployment, with opportunities to work on NLP, computer vision, generative AI, and intelligent automation across diverse industries.
Key Responsibilities
- Design, train, and deploy machine learning models for NLP, computer vision, recommendation systems, and other AI-driven use cases.
- Integrate ML models into production-ready web and mobile applications, ensuring scalability and reliability.
- Collaborate with data scientists to optimize algorithms, pipelines, and inference performance.
- Build APIs and microservices for model serving, monitoring, and scaling.
- Leverage cloud platforms (AWS, Azure, GCP) for ML workflows, containerization (Docker/Kubernetes), and CI/CD pipelines.
- Implement AI-powered features such as chatbots, personalization engines, predictive analytics, or automation systems.
- Develop and maintain ETL pipelines, data preprocessing workflows, and feature engineering processes.
- Ensure solutions meet security, compliance, and performance standards.
- Stay updated with the latest research and trends in deep learning, generative AI, and LLMs.
Skills & Qualifications
- Bachelor’s or Master’s in Computer Science, Machine Learning, Data Science, or related field.
- Proven experience of 4 years as an AI/ML Engineer, Data Scientist, or AI Application Developer.
- Strong programming skills in Python (TensorFlow, PyTorch, Scikit-learn); familiarity with LangChain, Hugging Face, OpenAI API is a plus.
- Experience in model deployment, serving, and optimization (FastAPI, Flask, Django, or Node.js).
- Proficiency with databases (SQL and NoSQL: MySQL, PostgreSQL, MongoDB).
- Hands-on experience with cloud ML services (SageMaker, Vertex AI, Azure ML) and DevOps tools (Docker, Kubernetes, CI/CD).
- Knowledge of MLOps practices: model versioning, monitoring, retraining, experiment tracking.
- Familiarity with frontend frameworks (React.js, Angular, Vue.js) for building AI-driven interfaces (nice to have).
- Strong understanding of data structures, algorithms, APIs, and distributed systems.
- Excellent problem-solving, analytical, and communication skills.
Job Title: AI / Machine Learning Engineer
Company: Apprication Pvt Ltd
Location: Goregaon East
Employment Type: Full-time
Experience: 4 Years
About the Role
We’re seeking a highly motivated AI / Machine Learning Engineer to join our growing engineering team. You will design, build, and deploy AI-powered solutions for web and application platforms, bringing cutting-edge machine learning research into real-world production systems.
This role blends applied machine learning, backend engineering, and cloud deployment, with opportunities to work on NLP, computer vision, generative AI, and intelligent automation across diverse industries.
Key Responsibilities
- Design, train, and deploy machine learning models for NLP, computer vision, recommendation systems, and other AI-driven use cases.
- Integrate ML models into production-ready web and mobile applications, ensuring scalability and reliability.
- Collaborate with data scientists to optimize algorithms, pipelines, and inference performance.
- Build APIs and microservices for model serving, monitoring, and scaling.
- Leverage cloud platforms (AWS, Azure, GCP) for ML workflows, containerization (Docker/Kubernetes), and CI/CD pipelines.
- Implement AI-powered features such as chatbots, personalization engines, predictive analytics, or automation systems.
- Develop and maintain ETL pipelines, data preprocessing workflows, and feature engineering processes.
- Ensure solutions meet security, compliance, and performance standards.
- Stay updated with the latest research and trends in deep learning, generative AI, and LLMs.
Skills & Qualifications
- Bachelor’s or Master’s in Computer Science, Machine Learning, Data Science, or related field.
- Proven experience of 4 years as an AI/ML Engineer, Data Scientist, or AI Application Developer.
- Strong programming skills in Python (TensorFlow, PyTorch, Scikit-learn); familiarity with LangChain, Hugging Face, OpenAI API is a plus.
- Experience in model deployment, serving, and optimization (FastAPI, Flask, Django, or Node.js).
- Proficiency with databases (SQL and NoSQL: MySQL, PostgreSQL, MongoDB).
- Hands-on experience with cloud ML services (SageMaker, Vertex AI, Azure ML) and DevOps tools (Docker, Kubernetes, CI/CD).
- Knowledge of MLOps practices: model versioning, monitoring, retraining, experiment tracking.
- Familiarity with frontend frameworks (React.js, Angular, Vue.js) for building AI-driven interfaces (nice to have).
- Strong understanding of data structures, algorithms, APIs, and distributed systems.
- Excellent problem-solving, analytical, and communication skills.
About Rekise Marine
Rekise Marine is a startup focused on sustainably enhancing the utility of oceans through autonomous robotic infrastructure. Our efforts center on developing advanced autonomous technology for the maritime industry, serving both defense and commercial sectors globally. We specialize in creating autonomous vessels both surface and underwater as well as autonomous port infrastructure. Currently, we are building the flagship autonomous platform of the Indian Navy.
Key Responsibilities
* Develop AI/ML pipelines for sonar/LiDAR/Radar and camera-based perception.
* Design multi-sensor fusion frameworks for obstacle detection, seabed mapping, and environmental awareness.
* Implement real-time object detection, segmentation, and tracking for underwater missions.
* Enhance robustness of perception under low-light, turbidity, and noisy acoustic conditions.
* Apply model optimization techniques (quantization, pruning, distillation, real-time deployment tuning) to ensure efficiency on embedded and resource-constrained systems.
Preferred Skills
* Experience with deep learning frameworks (PyTorch/TensorFlow).
* Strong knowledge of signal processing, computer vision, and sensor fusion.
* Proficiency in GPU acceleration, C++/Python, ROS/ROS2.
* Track record of published research or field deployments in underwater perception.
* Demonstrable full stack experience with ML based perception (data collection, annotation, training & edge inference).
Good to Have
* Publications in top-tier robotics/AI conferences or journals (e.g., ICRA, IROS, ICAR, CVPR, ICCV, NeurIPS).
* Hands-on experience with real-world Autonomous Systems (AGV/AUV/UAV), field trials, and deployments.
Why You’ll Love Working With Us
A chance to be part of a leading marine robotics startup in India.
Competitive salary.
Flexible and innovative work environment promoting collaboration.
A role where your contributions make a real difference and drive impact.
Opportunities for travel in relation to customer interactions and field testing
What We’re Looking For
As a Senior AI/ML Engineer at Meltwater, you’ll play a vital role in building cutting-edge social solutions for our global client base within the Explore mission. We’re seeking a proactive, quick-learning engineer who thrives in a collaborative environment.
Our culture values continuous learning, team autonomy, and a DevOps mindset. Meltwater development teams take full ownership of their subsystems and infrastructure, including running on-call rotations.
With a heavy reliance on Software Engineering in AI/ML and Data Science, we seek individuals with experience in:
- Cloud infrastructure and containerisation (Docker, Azure or AWS – Azure preferred)
- Data preparation
- Model lifecycle (training, serving, registries)
- Natural Language Processing (NLP) and Large Language Models (LLMs)
In this role, you’ll have the opportunity to:
- Push the boundaries of our technology stack
- Modify open-source libraries
- Innovate with existing technologies
- Work on distributed systems at scale
- Extract insights from vast amounts of data
What You’ll Do
- Lead and mentor a small team while doing hands-on coding.
- Demonstrate excellent communication and collaboration skills.
What You’ll Bring
- Bachelor’s or Master’s degree in Computer Science (or equivalent) OR demonstrable experience.
- Proven experience as a Lead Software Engineer in AI/ML and Data Science.
- 8+ years of working experience.
- 2+ years of leadership experience as Tech Lead or Team Lead.
- 5+ years strong knowledge of Python and software engineering principles.
- 5+ years strong knowledge of cloud infrastructure and containerization.
- Docker (required).
- Azure or AWS (required, Azure preferred).
- 5+ years strong working knowledge of TensorFlow / PyTorch.
- 3+ years good working knowledge of ML-Ops principles.
- Data preparation.
- Model lifecycle (training, serving, registries).
- Theoretical knowledge of AI / Data Science in one or more of:
- Natural Language Processing (NLP) and LLMs
- Neural Networks
- Topic modelling and clustering
- Time Series Analysis (TSA): anomaly detection, trend analysis, forecasting
- Retrieval Augmented Generation
- Speech to Text
- Excellent communication and collaboration skills.
What We Offer
- Flexible paid time off options for enhanced work-life balance.
- Comprehensive health insurance tailored for you.
- Employee assistance programs covering mental health, legal, financial, wellness, and behavioural support.
- Complimentary Calm App subscription for you and your loved ones.
- Energetic work environment with a hybrid work style.
- Family leave program that grows with your tenure.
- Inclusive community with professional development opportunities.
Our Story
At Meltwater, we believe that when you have the right people in the right environment, great things happen.
Our best-in-class technology empowers 27,000 customers worldwide to make better business decisions through data. But we can’t do that without our global team of developers, innovators, problem-solvers, and high-performers who embrace challenges and find new solutions.
Our award-winning global culture drives everything we do. Employees can make an impact, learn every day, feel a sense of belonging, and celebrate successes together.
We are innovators at the core who see potential in people, ideas, and technologies. Together, we challenge ourselves to go big, be bold, and build best-in-class solutions.
- 2,200+ employees
- 50 locations across 25 countries
We are Meltwater. We love working here, and we think you will too.
"Inspired by innovation, powered by people."
What You’ll Do:
As an AI/ML Engineer at Meltwater, you’ll play a vital role in building cutting-edge social solutions for our global client base within the Explore mission. We’re seeking a proactive, quick-learning engineer who thrives in a collaborative environment. Our culture values continuous learning, team autonomy, and a DevOps mindset.
Meltwater development teams take full ownership of their subsystems and infrastructure, including running on-call rotations. With a heavy reliance on Software Engineer in AI/ML and Data Science, we seek individuals with experience in:
- Cloud infrastructure and containerization (Docker, Azure or AWS is required; Azure is preferred)
- Data Preparation
- Model Lifecycle (training, serving, and registries)
- Natural Language Processing (NLP) and LLMs
In this role, you’ll have the opportunity to push the boundaries of our technology stack, from modifying open-source libraries to innovating with existing technologies. If you’re passionate about distributed systems at scale and finding new ways to extract insights from vast amounts of data, we invite you to join us in this exciting journey.
What You’ll Bring:
- Bachelor’s or master’s degree in computer science or equivalent degree or demonstrable experience.
- Proven experience as a Software Engineer in AI/ML and Data Science.
- Minimum of 2-4 years of working experience.
- Strong working experience in Python and software engineering principles (2+ Years).
- Experience with cloud infrastructure and containerization (1+ Years).
- Docker is required.
- Experience with TensorFlow / PyTorch (2+ Years).
- Experience with ML-Ops Principles (1+ Years).
- Data Preparation
- Model Lifecycle (training, serving, and registries)
- Sound knowledge on any cloud (AWS/Azure).
- Good theoretical knowledge of AI / Data Science in one or more of the following areas:
- Natural Language Processing (NLP) and LLMs
- Neural Networks
- Topic Modelling and Clustering
- Time Series Analysis (TSA), including anomaly detection, trend analysis, and forecasting
- Retrieval Augmented Generation
- Speech to Text
- Excellent communication and collaboration skills
What We Offer:
- Enjoy comprehensive paid time off options for enhanced work-life balance.
- Comprehensive health insurance tailored for you.
- Employee assistance programs covering mental health, legal, financial, wellness, and behaviour areas to ensure your overall well-being.
- Energetic work environment with a hybrid work style, providing the balance you need.
- Benefit from our family leave program, which grows with your tenure at Meltwater.
- Thrive within our inclusive community and seize ongoing professional development opportunities to elevate your career.
Where You’ll Work:
HITEC City, Hyderabad.
Our Story:
The sky is the limit at Meltwater.
At Meltwater, we believe that when you have the right people in the right working environment, great things happen. Our best-in-class technology empowers our 27,000 customers around the world to analyse over a billion pieces of data each day and make better business decisions.
Our award-winning culture is our north star and drives everything we do – from striving to create an environment where all employees do their best work, to delivering customer value by continuously innovating our products — and making sure to celebrate our successes and have fun along the way.
We’re proud of our diverse team of 2,300+ employees in 50 locations across 25 countries around the world. No matter where you are, you’ll work with people who care about your success and get the support you need to reach your goals.
So, in a nutshell, that’s Meltwater. We love working here, and we think you will too.
About Unilog
Unilog is the only connected product content and eCommerce provider serving the Wholesale Distribution, Manufacturing, and Specialty Retail industries. Our flagship CX1 Platform is at the center of some of the most successful digital transformations in North America. CX1 Platform’s syndicated product content, integrated eCommerce storefront, and automated PIM tool simplify our customers' path to success in the digital marketplace.
With more than 500 customers, Unilog is uniquely positioned as the leader in eCommerce and product content for Wholesale distribution, manufacturing, and specialty retail.
About the Role
We are looking for a highly motivated Innovation Engineer to join our CTO Office and drive the exploration, prototyping, and adoption of next-generation technologies. This role offers a unique opportunity to work at the forefront of AI/ML, Generative AI (Gen AI), Large Language Models (LLMs), Vertex AI, MCP, Vector Databases, AI Search, Agentic AI, Automation.
As an Innovation Engineer, you will be responsible for identifying emerging technologies, building proof-of-concepts (PoCs), and collaborating with cross-functional teams to define the future of AI-driven solutions. Your work will directly influence the company’s technology strategy and help shape disruptive innovations.
Key Responsibilities
- Research Implementation: Stay ahead of industry trends, evaluate emerging AI/ML technologies, and prototype novel solutions in areas like Gen AI, Vector Search, AI Agents, VertexAI, MCP and Automation.
- Proof-of-Concept Development: Rapidly build, test, and iterate PoCs to validate new technologies for potential business impact.
- AI/ML Engineering: Design and develop AI/ML models, AI Agents, LLMs, intelligent search capabilities leveraging Vector embeddings.
- Vector AI Search: Explore vector databases and optimize retrieval-augmented generation (RAG) workflows.
- Automation AI Agents: Develop autonomous AI agents and automation frameworks to enhance business processes.
- Collaboration Thought Leadership: Work closely with software developers and product teams to integrate innovations into production-ready solutions.
- Innovation Strategy: Contribute to the technology roadmap, patents, and research papers to establish leadership in emerging domains.
Required Qualifications
- 4–10 years of experience in AI/ML, software engineering, or a related field.
- Strong hands-on expertise in Python, TensorFlow, PyTorch, LangChain, Hugging Face, OpenAI APIs, Claude, Gemini, VertexAI, MCP.
- Experience with LLMs, embeddings, AI search, vector databases (e.g., Pinecone, FAISS, Weaviate, PGVector), MCP and agentic AI (Vertex, Autogen, ADK)
- Familiarity with cloud platforms (AWS, Azure, GCP) and AI/ML infrastructure.
- Strong problem-solving skills and a passion for innovation.
- Ability to communicate complex ideas effectively and work in a fast-paced, experimental environment.
Preferred Qualifications
- Experience with multi-modal AI (text, vision, audio), reinforcement learning, or AI security.
- Knowledge of data pipelines, MLOps, and AI governance.
- Contributions to open-source AI/ML projects or published research papers.
Why Join Us?
- Work on cutting-edge AI/ML innovations with the CTO Office.
- Influence the company’s future AI strategy and shape emerging technologies.
- Competitive compensation, growth opportunities, and a culture of continuous learning.
About Our Benefits
Unilog offers a competitive total rewards package including competitive salary, multiple medical, dental, and vision plans to meet all our employees’ needs, career development, advancement opportunities, annual merit, a generous time-off policy, and a flexible work environment.
Unilog is committed to building the best team and we are committed to fair hiring practices where we hire people for their potential and advocate for diversity, equity, and inclusion. As such, we do not discriminate or make decisions based on your race, color, religion, creed, ancestry, sex, national origin, age, disability, familial status, marital status, military status, veteran status, sexual orientation, gender identity, or expression, or any other protected class.
About Moative
Moative, an Applied AI Services company, designs AI roadmaps, builds co-pilots, and develops agentic AI solutions for companies across industries including energy and utilities.
Through Moative Labs, we aspire to build AI-led products and launch AI startups in vertical markets.
Our Past: We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League alumni, ex-Googlers, and successful entrepreneurs.
Business Context
Moative is looking for a Data Science Project Manager to lead a long-term engagement for a Houston-based utilities company. As part of this engagement, we will develop advanced AI/ML models for load forecasting, energy pricing, trading strategies, and related areas.
We have a high-performing team of data scientists and ML engineers based in Chennai, India, along with an on-site project manager in Houston, TX.
Work You’ll Do
As a Data Science Project Manager, you’ll wear two hats. On one hand, you’ll act as a project manager — engaging with clients, understanding business priorities, and discussing solution or algorithm approaches. You will coordinate with the on-site project manager to manage timelines and ensure quality delivery. You’ll also handle client communication, setting expectations, gathering feedback, and keeping the engagement in good health.
On the other hand, you’ll act as a senior data scientist — overseeing junior data scientists and analysts, guiding the offshore team on data science, engineering, and business challenges, and providing expertise in statistical and mathematical concepts, algorithms, and model development.
The ideal candidate has a strong background in statistics, machine learning, and programming, along with business acumen and project management skills.
Responsibilities
- Client Engagement: Act as the primary point of contact for clients on data science requirements. Support the on-site PM in managing client needs and build strong stakeholder relationships.
- Project Coordination: Lead the offshore team, ensure alignment on project goals, and work with clients to define scope and deliverables.
- Team Management: Supervise the offshore AI/ML team, ensure milestones are met, and provide domain/technical guidance.
- Data Science Leadership: Mentor teams, create frameworks for scalable solutions, and drive adoption of best practices in AI/ML lifecycle.
- Quality Assurance: Work with the offshore PM to implement QA processes that ensure accuracy and reliability.
- Risk Management: Identify risks and develop mitigation strategies.
- Stakeholder Communication: Provide regular updates on progress, challenges, and achievements.
Who You Are
You are a Project Manager passionate about delivering high-quality, data-driven solutions through robust project management practices. You have experience managing data-heavy projects in an onsite-offshore model with significant client engagement. You also bring some hands-on experience in data science and analytics, preferably in energy/utilities or financial risk/trading. You thrive in ambiguity, take initiative, and can confidently defend your decisions.
Requirements & Skills
- 8+ years of experience applying data science methods to real-world data, ideally in Energy & Utilities or financial risk/commodities trading.
- 3+ years of experience leading data science teams delivering AI/ML solutions.
- Deep familiarity with a range of methods and algorithms: time-series analysis, regression, experimental design, optimization, etc.
- Strong understanding of ML algorithms, including deep learning, neural networks, NLP, and more.
- Proficient in cloud platforms (AWS, Azure, GCP), ML frameworks (TensorFlow, PyTorch), and MLOps platforms (MLflow, etc.).
- Broad understanding of data structures, data engineering, and architectures.
- Strong interpersonal skills: result-oriented, proactive, and capable of handling multiple projects.
- Ability to collaborate effectively, take accountability, and stay composed under stress.
- Excellent verbal and written communication skills for both technical and non-technical stakeholders.
- Proven ability to identify and resolve issues quickly and efficiently.
Working at Moative
Moative is a young company, but we believe in thinking long-term while acting with urgency. Our ethos is rooted in innovation, efficiency, and high-quality outcomes. We believe the future of work is AI-augmented and boundaryless.
Guiding Principles
- Think in decades. Act in hours. Decisions for the long-term, execution in hours/days.
- Own the canvas. Fix or improve anything not done right, regardless of who did it.
- Use data or don’t. Avoid political “cover-my-back” use of data; balance intuition with data-driven approaches.
- Avoid work about work. Keep processes lean; meetings should be rare and purposeful.
- High revenue per person. Default to automation, multi-skilling, and high-quality output instead of unnecessary hiring.
Additional Details
The position is based out of Chennai and involves significant in-person collaboration. Applicants should demonstrate being in the 90th percentile or above, whether through top institutions, awards/accolades, or consistent outstanding performance.
If this role excites you, we encourage you to apply — even if you don’t check every box.
We’re seeking a highly skilled, execution-focused Data Scientist with 4–10 years of experience to join our team. This role demands hands-on expertise in fine-tuning and deploying generative AI models across image, video, and audio domains — with a special focus on lip-sync, character consistency, and automated quality evaluation frameworks. You will be expected to run rapid experiments, test architectural variations, and deliver working model iterations quickly in a high-velocity R&D environment.
Responsibilities
- Run end-to-end fine-tuning experiments on state-of-the-art models (Flux family, LoRA, diffusion-based architectures, context-based composition).
- Develop and optimize generative AI models for audio generation and lip-sync, ensuring high fidelity and natural delivery.
- Extend current language models to support regional Indian languages beyond US/UK English for audio and content generation.
- Enable emotional delivery in generated audio (shouting, crying, whispering) to enhance realism.
- Integrate and synchronize background scores seamlessly with generated video content.
- Work towards achieving video quality standards comparable to Veo3/Sora.
- Ensure consistency in scenes and character generation across multiple outputs.
- Design and implement an automated objective evaluation frameworks to replace subjective human review — for cover images, video frames, and audio clips. Implement scoring systems that standardize quality checks before editorial approval.
- Run comparative tests across multiple model architectures to evaluate trade-offs in quality, speed, and efficiency.
- Drive initiatives independently, showcasing high agency and accountability. Utilize strong first-principle thinking to tackle complex challenges.
- Apply a research-first approach with rapid experimentation in the fast-evolving Generative AI space.
Requirements
- 4-10 years of experience in Data Science, with a strong focus on Generative AI.
- Familiarity with state-of-the-art models in generative AI (e.g., Flux, diffusion models, GANs).
- Proven expertise in developing and deploying models for audio and video generation.
- Demonstrated experience with natural language processing (NLP), especially for regional language adaptation.
- Experience with model fine-tuning and optimization techniques.
- Hands-on exposure to ML deployment pipelines (FastAPI or equivalent).
- Strong programming skills in Python and relevant deep learning frameworks (e.g., TensorFlow, PyTorch).
- Experience in designing and implementing automated evaluation metrics for generative content.
- A portfolio or demonstrable experience in projects related to content generation, lip-sync, or emotional AI is a plus.
- Exceptional problem-solving skills and a proactive approach to research and experimentation.
Benefits
- Best in class salary: We hire only the best, and we pay accordingly.
- Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field.
- Keep on learning with a world-class team: Work with the best in the field, challenge yourself constantly, and learn something new every day.
About us
Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world! We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore. Since 2019, Proximity has created and grown high-impact, scalable products used by 370 million daily users, with a total net worth of $45.7 billion among our client companies.
Today, we are a global team of coders, designers, product managers, geeks, and experts. We solve complex problems and build cutting-edge tech, at scale. Our team of Proxonauts is growing quickly, which means your impact on the company’s success will be huge. You’ll have the chance to work with experienced leaders who have built and led multiple tech, product, and design teams.
Certa (getcerta.com) is a Silicon Valley-based startup automating the vendor, supplier, and stakeholder onboarding processes for businesses globally. Serving Fortune 500 and Fortune 1000 clients, Certa's engineering team tackles expansive and deeply technical challenges, driving innovation in business processes across industries.
Location: Remote (India only)
Role Overview
We are looking for an experienced and innovative AI Engineer to join our team and push the boundaries of large language model (LLM) technology to drive significant impact in our products and services . In this role, you will leverage your strong software engineering skills (particularly in Python and cloud-based backend systems) and your hands-on experience with cutting-edge AI (LLMs, prompt engineering, Retrieval-Augmented Generation, etc.) to build intelligent features for enterprise (B2B SaaS). As an AI Engineer on our team, you will design and deploy AI-driven solutions (such as LLM-powered agents and context-aware systems) from prototype to production, iterating quickly and staying up-to-date with the latest developments in the AI space . This is a unique opportunity to be at the forefront of a new class of engineering roles that blend robust backend system design with state-of-the-art AI integration, shaping the future of user experiences in our domain.
Key Responsibilities
- Design and Develop AI Features: Lead the design, development, and deployment of generative AI capabilities and LLM-powered services that deliver engaging, human-centric user experiences . This includes building features like intelligent chatbots, AI-driven recommendations, and workflow automation into our products.
- RAG Pipeline Implementation: Design, implement, and continuously optimize end-to-end RAG (Retrieval-Augmented Generation) pipelines, including data ingestion and parsing, document chunking, vector indexing, and prompt engineering strategies to provide relevant context to LLMs . Ensure that our AI systems can efficiently retrieve and use information from knowledge bases to enhance answer accuracy.
- Build LLM-Based Agents: Develop and refine LLM-based agentic systems that can autonomously perform complex tasks or assist users in multi-step workflows. Incorporate tools for planning, memory, and context management (e.g. long-term memory stores, tool use via APIs) to extend the capabilities of our AI agents . Experiment with emerging best practices in agent design (planning algorithms, self-healing loops, etc.) to make these agents more reliable and effective.
- Integrate with Product Teams: Work closely with product managers, designers, and other engineers to integrate AI capabilities seamlessly into our products, ensuring that features align with user needs and business goals . You’ll collaborate cross-functionally to translate product requirements into AI solutions, and iterate based on feedback and testing.
- System Evaluation & Iteration: Rigorously evaluate the performance of AI models and pipelines using appropriate metrics – including accuracy/correctness, response latency, and avoidance of errors like hallucinations . Conduct thorough testing and use user feedback to drive continuous improvements in model prompts, parameters, and data processing.
- Code Quality & Best Practices: Write clean, maintainable, and testable code while following software engineering best practices . Ensure that the AI components are well-structured, scalable, and fit into our overall system architecture. Implement monitoring and logging for AI services to track performance and reliability in production.
- Mentorship and Knowledge Sharing: Provide technical guidance and mentorship to team members on best practices in generative AI development . Help educate and upskill colleagues (e.g. through code reviews, tech talks) in areas like prompt engineering, using our AI toolchain, and evaluating model outputs. Foster a culture of continuous learning and experimentation with new AI technologies.
- Research & Innovation: Continuously explore the latest advancements in AI/ML (new model releases, libraries, techniques) and assess their potential value for our products . You will have the freedom to prototype innovative solutions – for example, trying new fine-tuning methods or integrating new APIs – and bring those into our platform if they prove beneficial. Staying current with emerging research and industry trends is a key part of this role .
Required Skills and Qualifications
- Software Engineering Experience: 3+ years (Mid-level) / 5+ years (Senior) of professional software engineering experience. Rock-solid backend development skills with expertise in Python and designing scalable APIs/services. Experience building and deploying systems on AWS or similar cloud platforms is required (including familiarity with cloud infrastructure and distributed computing) . Strong system design abilities with a track record of designing robust, maintainable architectures is a must.
- LLM/AI Application Experience: Proven experience building applications that leverage large language models or generative AI. You have spent time prompting and integrating language models into real products (e.g. building chatbots, semantic search, AI assistants) and understand their behavior and failure modes . Demonstrable projects or work in LLM-powered application development – especially using techniques like RAG or building LLM-driven agents – will make you stand out .
- AI/ML Knowledge: Prioritize applied LLM product engineering over traditional ML pipelines. Strong chops in prompt design, function calling/structured outputs, tool use, context-window management, and the RAG levers that matter (document parsing/chunking, metadata, re-ranking, embedding/model selection). Make pragmatic model/provider choices (hosted vs. open) using latency, cost, context length, safety, and rate-limit trade-offs; know when simple prompting/config changes beat fine-tuning, and when lightweight adapters or fine-tuning are justified. Design evaluation that mirrors product outcomes: golden sets, automated prompt unit tests, offline checks, and online A/Bs for helpfulness/correctness/safety; track production proxies like retrieval recall and hallucination rate. Solid understanding of embeddings, tokenization, and vector search fundamentals, plus working literacy in transformers to reason about capabilities/limits. Familiarity with agent patterns (planning, tool orchestration, memory) and guardrail/safety techniques.
- Tooling & Frameworks: Hands-on experience with the AI/LLM tech stack and libraries. This includes proficiency with LLM orchestration libraries such as LangChain, LlamaIndex, etc., for building prompt pipelines . Experience working with vector databases or semantic search (e.g. Pinecone, Chroma, Milvus) to enable retrieval-augmented generation is highly desired.
- Cloud & DevOps: Own the productionization of LLM/RAG-backed services as high-availability, low-latency backends. Expertise in AWS (e.g., ECS/EKS/Lambda, API Gateway/ALB, S3, DynamoDB/Postgres, OpenSearch, SQS/SNS/Step Functions, Secrets Manager/KMS, VPC) and infrastructure-as-code (Terraform/CDK). You’re comfortable shipping stateless APIs, event-driven pipelines, and retrieval infrastructure (vector stores, caches) with strong observability (p95/p99 latency, distributed tracing, retries/circuit breakers), security (PII handling, encryption, least-privilege IAM, private networking to model endpoints), and progressive delivery (blue/green, canary, feature flags). Build prompt/config rollout workflows, manage token/cost budgets, apply caching/batching/streaming strategies, and implement graceful fallbacks across multiple model providers.
- Product and Domain Experience: Experience building enterprise (B2B SaaS) products is a strong plus . This means you understand considerations like user experience, scalability, security, and compliance. Past exposure to these types of products will help you design AI solutions that cater to a range of end-users.
- Strong Communication & Collaboration: Excellent interpersonal and communication skills, with an ability to explain complex AI concepts to non-technical stakeholders and create clarity from ambiguity . You work effectively in cross-functional teams and can coordinate with product, design, and ops teams to drive projects forward.
- Problem-Solving & Autonomy: Self-motivated and able to manage multiple priorities in a fast-paced environment . You have a demonstrated ability to troubleshoot complex systems, debug issues across the stack, and quickly prototype solutions. A “figure it out” attitude and creative approach to overcoming technical challenges are key.
Preferred (Bonus) Qualifications
- Multi-Modal and Agents: Experience developing complex agentic systems using LLMs (for example, multi-agent systems or integrating LLMs with tool networks) is a bonus . Similarly, knowledge of multi-modal AI (combining text with vision or other data) could be useful as we expand our product capabilities.
- Startup/Agile Environment: Prior experience in an early-stage startup or similarly fast-paced environment where you’ve worn multiple hats and adapted to rapid changes . This role will involve quick iteration and evolving requirements, so comfort with ambiguity and agility is valued.
- Community/Research Involvement: Active participation in the AI community (open-source contributions, research publications, or blogging about AI advancements) is appreciated. It demonstrates passion and keeps you at the cutting edge. If you have published research or have a portfolio of AI side projects, let us know !
Perks of working at Certa.ai:
- Best-in-class compensation
- Fully-remote work with flexible schedules
- Continuous learning
- Massive opportunities for growth
- Yearly offsite
- Quarterly hacker house
- Comprehensive health coverage
- Parental Leave
- Latest Tech Workstation
- Rockstar team to work with (we mean it!)
Job Description – AI Developer
Job Description
We are seeking a forward-thinking AI Developer with expertise in Generative AI, Machine Learning, Data Science, and Advanced Analytics. In this role, you will design, optimize, and deploy scalable AI solutions that power automation, personalization, and decision intelligence. You will closely collaborate with data engineers, product leaders, and business stakeholders to develop production-grade AI systems aligned with the latest enterprise AI trends such as LLM, prompt engineering, multimodal AI, and trustworthy/ethical AI practices.
This is a unique opportunity to work at the forefront of AI innovation, shaping high-impact solutions that address real-world challenges across industries.
Key Responsibilities
- Design and deploy advanced Generative AI models including LLMs, diffusion models, and multimodal architectures.
- Develop and fine-tune ML/DL solutions for NLP, computer vision, time-series forecasting, and predictive analytics.
- Implement RAG pipelines, embeddings-based search, and knowledge graph integrations to enhance context-aware AI applications.
- Stay ahead of AI research, industry trends, and tools (multi-agent systems, federated learning, privacy-preserving ML).
What we are looking for
- Strong programming background in Python (primary), R & Familiar with Object Oriented Programming Language.
- Proficiency in any of the framework PyTorch, TensorFlow, SAS, ChemBerta.
- Expertise in Machine Learning & Deep Learning.
- Strong grounding in mathematics & applied statistics (linear algebra, probability, optimization).
Qualifications
- Bachelor’s, Master’s, in Computer Science, Artificial Intelligence, Data Science, or related fields. We also welcome PhD scholars.
- 0–6 years of proven experience into AI development, optimization, and production deployment.
Preferred / Nice to Have
- Someone who is passionate about GEN AI is ideal candidate & did Research contributions or open-source AI project contributions.
- Exposure to multimodal AI, agent-based systems, or reinforcement learning.
- Knowledge of AI safety, interpretability frameworks, and responsible AI practices.
Job Title: AI Architecture Intern
Company: PGAGI Consultancy Pvt. Ltd.
Location: Remote
Employment Type: Internship
Position Overview
We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.
Duration: 6 months
Key Responsibilities:
- AI System Architecture Design: Collaborate with the technical team to design robust, scalable, and high-performance AI system architectures aligned with client requirements.
- Client-Focused Solutions: Analyze and interpret client needs to ensure architectural solutions meet expectations while introducing innovation and efficiency.
- Methodology Development: Assist in the formulation and implementation of best practices, methodologies, and frameworks for sustainable AI system development.
- Technology Stack Selection: Support the evaluation and selection of appropriate tools, technologies, and frameworks tailored to project objectives and future scalability.
- Team Collaboration & Learning: Work alongside experienced AI professionals, contributing to projects while enhancing your knowledge through hands-on involvement.
Requirements:
- Strong understanding of AI concepts, machine learning algorithms, and data structures.
- Familiarity with AI development frameworks (e.g., TensorFlow, PyTorch, Keras).
- Proficiency in programming languages such as Python, Java, or C++.
- Demonstrated interest in system architecture, design thinking, and scalable solutions.
- Up-to-date knowledge of AI trends, tools, and technologies.
- Ability to work independently and collaboratively in a remote team environment
Perks:
- Hands-on experience with real AI projects.
- Mentoring from industry experts.
- A collaborative, innovative and flexible work environment
Compensation:
- Joining Bonus: A one-time bonus of INR 2,500 will be awarded upon joining.
- Stipend: Base is INR 8000/- & can increase up to 20000/- depending upon performance matrix.
After completion of the internship period, there is a chance to get a full-time opportunity as an AI/ML engineer (Up to 12 LPA).
Preferred Experience:
- Prior experience in roles such as AI Solution Architect, ML Architect, Data Science Architect, or AI/ML intern.
- Exposure to AI-driven startups or fast-paced technology environments.
- Proven ability to operate in dynamic roles requiring agility, adaptability, and initiative.
Senior Machine Learning Engineer
📍 Location: Remote
💼 Type: Full-Time
💰 Salary: $800 - $1,000 USD / month
Apply at: https://forms.gle/Fwti67UeTEkx2Kkn6
About Us
At Momenta, we're committed to creating a safer digital world by protecting individuals and businesses from voice-based fraud and scams. Through innovative AI technology and community collaboration, we're building a future where communication is secure and trustworthy.
Position Overview
We’re hiring a Senior Machine Learning Engineer with deep expertise in audio signal processing and neural network-based detection. The selected engineer will be responsible for delivering a production-grade, real-time deepfake detection pipeline as part of a time-sensitive, high-stakes 3-month pilot deployment.
Key Responsibilities
📌 Design and Deliver Core Detection Pipeline
Lead the development of a robust, modular deepfake detection pipeline capable of ingesting, processing, and classifying real-time audio streams with high accuracy and low latency. Architect the system to operate under telecom-grade conditions with configurable interfaces and scalable deployment strategies.
📌 Model Strategy, Development, and Optimization
Own the experimentation and refinement of state-of-the-art deep learning models for voice fraud detection. Evaluate multiple model families, benchmark performance across datasets, and strategically select or ensemble models that balance precision, robustness, and compute efficiency for real-world deployment.
📌 Latency-Conscious Production Readiness
Ensure the entire detection stack meets strict performance targets, including sub-20ms inference latency. Apply industry best practices in model compression, preprocessing optimization, and system-level integration to support high-throughput inference on both CPU and GPU environments.
📌 Evaluation Framework and Continuous Testing
Design and implement a comprehensive evaluation suite to validate model accuracy, false positive rates, and environmental robustness. Conduct rigorous testing across domains, including cross-corpus validation, telephony channel effects, adversarial scenarios, and environmental noise conditions.
📌 Deployment Engineering and API Integration
Deliver a fully containerized, production-ready inference service with REST/gRPC endpoints. Build CI/CD pipelines, integration tests, and monitoring hooks to ensure system integrity, traceability, and ease of deployment across environments.
Required Skills & Qualifications
🎯 Technical Skills:
ML Frameworks: PyTorch, TensorFlow, ONNX, OpenVINO, TorchScript
Audio Libraries: Librosa, Torchaudio, FFmpeg
Model Development: CNNs, Transformers, Wav2Vec/WavLM, AASIST, RawNet
Signal Processing: VAD, noise reduction, band-pass filtering, codec simulation
Optimization: Quantization, pruning, GPU acceleration
DevOps: Git, Docker, CI/CD, FastAPI or Flask, REST/gRPC
🎯 Preferred Experience:
Prior work on audio deepfake detection or telephony speech processing
Experience with real-time ML model deployment
Understanding of adversarial robustness and domain adaptation
Familiarity with call center environments or telecom-grade constraints
Compensation & Career Path:
Competitive pay based on experience and capability. ($800 - $1,000 USD / month)
Full-time with potential for conversion to a core team role.
Opportunity to lead future research and production deployments as part of our AI division.
Why Join Momenta?
Solve a global security crisis with cutting-edge AI.
Own a deliverable that will ship into production at scale.
Join a fast-growing team with seasoned founders and engineers.
Fully remote, high-autonomy environment focused on deep work.
🚀 Apply now and help shape the future of voice security
Technical Expertise
- Advanced proficiency in Python
- Expertise in Deep Learning Frameworks: PyTorch and TensorFlow
- Experience with Computer Vision Models:
- YOLO (Object Detection)
- UNet, Mask R-CNN (Segmentation)
- Deep SORT (Object Tracking)
Real-Time & Deployment Skills
- Real-time video analytics and inference optimization
- Model pipeline development using:
- Docker
- Git
- MLflow or similar tools
- Image processing proficiency: OpenCV, NumPy
- Deployment experience on Linux-based GPU systems and edge devices (Jetson Nano, Google Coral, etc.)
Professional Background
- Minimum 4+ years of experience in AI/ML, with a strong focus on Computer Vision and System-Level Design
- Educational qualification: B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or a related field
- Strong project portfolio or experience in production-level deployments
A Concise Glimpse into the Role
We’re on the hunt for young, energetic, and hustling talent ready to bring fresh ideas and unstoppable drive to the table.
This isn’t just another role—it’s a launchpad for change-makers. If you’re driven to disrupt, innovate, and challenge the norm, we want you to make your mark with us.
Are you ready to redefine the future?
Apply now and step into a career where your ideas power the impossible!
Your Time Will Be Invested In
· AI/ML Model Innovation and Research
· Are you ready to lead transformative projects at the cutting edge of AI and machine learning? We're looking for a visionary mind with a passion for building ground breaking solutions that redefine the possible.
What You'll Own
Pioneering AI/ML Model Innovation
· Take ownership of designing, developing, and deploying sophisticated AI and ML models that push boundaries.
· Spearhead the creation of generative AI applications that revolutionize real-world experiences.
· Drive end-to-end implementation of AI-driven products with a focus on measurable impact.
Data Engineering and Advanced Development
· Architect robust pipelines for data collection, pre-processing, and analysis, ensuring precision at every stage.
· Deliver clean, scalable, and high-performance Python code that empowers our AI systems to excel.
Trailblazing Research and Strategic Collaboration
· Dive into the latest research to stay ahead of AI/ML trends, identifying opportunities to integrate state-of-the-art techniques.
· Foster innovation by brainstorming with a dynamic team to conceptualize novel AI solutions.
· Elevate the team's expertise by preparing insightful technical documentation and presenting actionable findings.
What We Want You to Have
· 1-2 years' experience with live AI project experience, from conceptualization to real-world deployment.
· Foundational knowledge in AI, ML, and generative AI applications.
· Proficient in Python and familiar with libraries like TensorFlow, PyTorch, Scikit-learn.
· Experience working with structured & unstructured data, as well as predictive analytics.
· Basic understanding of Deep Learning Techniques.
· Knowledge of AutoGen for building scalable multi-agent AI systems & familiarity with LangChain or similar frameworks for building AI Agents.
· Knowledge of using AI tools like VS Copilot.
· Proficient in working with vector databases for managing and retrieving data.
· Understanding of AI/ML deployment tools such as Docker, Kubernetes.
· Understanding JavaScript, TypeScript with React and Tailwind.
· Proficiency in Prompt Engineering for various use cases, including content generation and data extraction.
· Ability to work independently and as part of a collaborative team.
· Excellent communication skills and a strong willingness to learn.
Nice to Have
· Prior project or coursework experience in AI/ML.
· Background in Big Data technologies (Spark, Hadoop, Databricks).
· Experience with containerization and deployment tools.
· Proficiency in SQL & NoSQL databases.
· Familiarity with Data Visualization tools (e.g., Matplotlib, Seaborn).
Soft Skills
· Strong problem-solving and analytical capabilities.
· Excellent teamwork and interpersonal communication.
· Ability to thrive in a fast-paced and innovation-driven environment.

Role : AIML Engineer
Location : Madurai
Experience : 5 to 10 Yrs
Mandatory Skills : AIML, Python, SQL, ML Models, PyTorch, Pandas, Docker, AWS
Language: Python
DBs : SQL
Core Libraries:
Time Series & Forecasting: pmdarima, statsmodels, Prophet, GluonTS, NeuralProphet
SOTA ML : ML Models, Boosting & Ensemble models etc.
Explainability : Shap / Lime
Required skills:
- Deep Learning: PyTorch, PyTorch Forecasting,
- Data Processing: Pandas, NumPy, Polars (optional), PySpark
- Hyperparameter Tuning: Optuna, Amazon SageMaker Automatic Model Tuning
- Deployment & MLOps: Batch & Realtime with API endpoints, MLFlow
- Serving: TorchServe, Sagemaker endpoints / batch
- Containerization: Docker
- Orchestration & Pipelines: AWS Step Functions, AWS SageMaker Pipelines
AWS Services:
- SageMaker (Training, Inference, Tuning)
- S3 (Data Storage)
- CloudWatch (Monitoring)
- Lambda (Trigger-based Inference)
- ECR, ECS or Fargate (Container Hosting)
We're hiring a skilled AI Developer to join our growing team at Geo Wave Pvt Ltd, based in Malé, Maldives. You’ll lead the development of smart automation tools, reporting dashboards, and AI systems to optimize our internal operations across fuel, logistics, and finance.
Responsibilities:
- Build and deploy AI-powered business tools
- Implement OCR/NLP solutions for document automation
- Create custom dashboards and backend APIs
- Automate workflows for reporting, inventory, and sales tracking
Must-Have Skills:
Python, Flask/FastAPI, TensorFlow/PyTorch, OCR/NLP, API development
Good-to-Have:
React.js, PostgreSQL, AWS/GCP, Docker
About Us
Alfred Capital - Alfred Capital is a next-generation on-chain proprietary quantitative trading technology provider, pioneering fully autonomous algorithmic systems that reshape trading and capital allocation in decentralized finance.
As a sister company of Deqode — a 400+ person blockchain innovation powerhouse — we operate at the cutting edge of quant research, distributed infrastructure, and high-frequency execution.
What We Build
- Alpha Discovery via On‑Chain Intelligence — Developing trading signals using blockchain data, CEX/DEX markets, and protocol mechanics.
- DeFi-Native Execution Agents — Automated systems that execute trades across decentralized platforms.
- ML-Augmented Infrastructure — Machine learning pipelines for real-time prediction, execution heuristics, and anomaly detection.
- High-Throughput Systems — Resilient, low-latency engines that operate 24/7 across EVM and non-EVM chains tuned for high-frequency trading (HFT) and real-time response
- Data-Driven MEV Analysis & Strategy — We analyze mempools, order flow, and validator behaviors to identify and capture MEV opportunities ethically—powering strategies that interact deeply with the mechanics of block production and inclusion.
Evaluation Process
- HR Discussion – A brief conversation to understand your motivation and alignment with the role.
- Initial Technical Interview – A quick round focused on fundamentals and problem-solving approach.
- Take-Home Assignment – Assesses research ability, learning agility, and structured thinking.
- Assignment Presentation – Deep-dive into your solution, design choices, and technical reasoning.
- Final Interview – A concluding round to explore your background, interests, and team fit in depth.
- Optional Interview – In specific cases, an additional round may be scheduled to clarify certain aspects or conduct further assessment before making a final decision.
Blockchain Data & ML Engineer
As a Blockchain Data & ML Engineer, you’ll work on ingesting and modeling on-chain behavior, building scalable data pipelines, and designing systems that support intelligent, autonomous market interaction.
What You’ll Work On
- Build and maintain ETL pipelines for ingesting and processing blockchain data.
- Assist in designing, training, and validating machine learning models for prediction and anomaly detection.
- Evaluate model performance, tune hyperparameters, and document experimental results.
- Develop monitoring tools to track model accuracy, data drift, and system health.
- Collaborate with infrastructure and execution teams to integrate ML components into production systems.
- Design and maintain databases and storage systems to efficiently manage large-scale datasets.
Ideal Traits
- Strong in data structures, algorithms, and core CS fundamentals.
- Proficiency in any programming language
- Curiosity about how blockchain systems and crypto markets work under the hood.
- Self-motivated, eager to experiment and learn in a dynamic environment.
Bonus Points For
- Hands-on experience with pandas, numpy, scikit-learn, or PyTorch.
- Side projects involving automated ML workflows, ETL pipelines, or crypto protocols.
- Participation in hackathons or open-source contributions.
What You’ll Gain
- Cutting-Edge Tech Stack: You'll work on modern infrastructure and stay up to date with the latest trends in technology.
- Idea-Driven Culture: We welcome and encourage fresh ideas. Your input is valued, and you're empowered to make an impact from day one.
- Ownership & Autonomy: You’ll have end-to-end ownership of projects. We trust our team and give them the freedom to make meaningful decisions.
- Impact-Focused: Your work won’t be buried under bureaucracy. You’ll see it go live and make a difference in days, not quarters
What We Value:
- Craftsmanship over shortcuts: We appreciate engineers who take the time to understand the problem deeply and build durable solutions—not just quick fixes.
- Depth over haste: If you're the kind of person who enjoys going one level deeper to really "get" how something works, you'll thrive here.
- Invested mindset: We're looking for people who don't just punch tickets, but care about the long-term success of the systems they build.
- Curiosity with follow-through: We admire those who take the time to explore and validate new ideas, not just skim the surface.
Compensation:
- INR 6 - 12 LPA
- Performance Bonuses: Linked to contribution, delivery, and impact.
Key Responsibilities :
- Algorithm Development : Design and optimize computer vision and deep learning algorithms for 3D applications.
- Model Deployment : Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment on edge devices after optimization to meet customer requirements
- Research and Innovation : Prototype new solutions based on the latest advancements in AI, machine learning, and computer vision.
- Cross-Functional Collaboration : Integrate algorithms into 3D rendering systems and work closely with the team to meet project goals. Collaborate with hardware engineers to fine-tune models for power, latency, and throughput constraints
- Documentation : Maintain code quality and document solutions for easy reference.
Qualifications :
- Experience : 3 or 3+ years in computer vision, deep learning, and AI.
- Education : Bachelor's or Master's in Computer Science, Data Science, Electrical Engineering, or related field.
Technical Skills :
- Proficiency in C, C++, OpenGL, Objective C, Swift, Python, PyTorch, TensorFlow, and OpenCV.
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- Knowledge of algorithms and data structures relevant to computer vision.
- Hands-on experience with NVIDIA platforms IGX, Jetson, or Xavier. (Experience with NVIDIA SDKs (e.g., DeepStream, TensorRT, CUDA, TAO Toolkit)
- Concepts of parallel architecture on GPU is an added advantage.
- Knowledge in linear algebra, calculus, and statistics
- Preferred : Knowledge of AR/VR, 3D vision, and AWS (SageMaker, Lambda, EC2, S3, RDS), CI/CD, Terraform, Docker, and Kubernetes)
You will:
- Collaborate with the I-Stem Voice AI team and CEO to design, build and ship new agent capabilities
- Develop, test and refine end-to-end voice agent models (ASR, NLU, dialog management, TTS)
- Stress-test agents in noisy, real-world scenarios and iterate for improved robustness and low latency
- Research and prototype cutting-edge techniques (e.g. robust speech recognition, adaptive language understanding)
- Partner with backend and frontend engineers to seamlessly integrate AI components into live voice products
- Monitor agent performance in production, analyze failure cases, and drive continuous improvement
- Occasionally demo our Voice AI solutions at industry events and user forums
You are:
- An AI/Software Engineer with hands-on experience in speech-centric ML (ASR, NLU or TTS)
- Skilled in building and tuning transformer-based speech models and handling real-time audio pipelines
- Obsessed with reliability: you design experiments to push agents to their limits and root-cause every error
- A clear thinker who deconstructs complex voice interactions from first principles
- Passionate about making voice technology inclusive and accessible for diverse users
- Comfortable moving fast in a small team, yet dogged about code quality, testing and reproducibility
Job Title : Senior Machine Learning Engineer
Experience : 8+ Years
Location : Chennai
Notice Period : Immediate Joiners Only
Work Mode : Hybrid
Job Summary :
We are seeking an experienced Machine Learning Engineer with a strong background in Python, ML algorithms, and data-driven development.
The ideal candidate should have hands-on experience with popular ML frameworks and tools, solid understanding of clustering and classification techniques, and be comfortable working in Unix-based environments with Agile teams.
Mandatory Skills :
- Programming Languages : Python
- Machine Learning : Strong experience with ML algorithms, models, and libraries such as Scikit-learn, TensorFlow, and PyTorch
- ML Concepts : Proficiency in supervised and unsupervised learning, including techniques such as K-Means, DBSCAN, and Fuzzy Clustering
- Operating Systems : RHEL or any Unix-based OS
- Databases : Oracle or any relational database
- Version Control : Git
- Development Methodologies : Agile
Desired Skills :
- Experience with issue tracking tools such as Azure DevOps or JIRA.
- Understanding of data science concepts.
- Familiarity with Big Data algorithms, models, and libraries.
What You'll Do:
Design, develop, and deploy machine learning models for real-world applications
Work with large datasets, perform data preprocessing, feature engineering, and model evaluation
Collaborate with cross-functional teams to integrate ML solutions into production
Stay up to date with the latest ML/AI research and technologies
What We’re Looking For:
Solid experience with Python and popular ML libraries (e.g., scikit-learn, TensorFlow, PyTorch)
Experience with data pipelines, model deployment, and performance tuning
Familiarity with cloud platforms (AWS/GCP/Azure) is a plus
Strong problem-solving and analytical skills
Excellent communication and teamwork abilities
Job Title: AI & ML Developer
Experience: 1+ Years
Location: Hyderabad
Company: VoltusWave Technologies India Private Limited
Job Summary:
We are looking for a passionate and skilled AI & Machine Learning Developer with over 1 year of experience to join our growing team. You will be responsible for developing, implementing, and maintaining ML models and AI-driven applications that solve real-world business problems.
Key Responsibilities:
- Design, build, and deploy machine learning models and AI solutions.
- Work with large datasets to extract meaningful insights and develop algorithms.
- Preprocess, clean, and transform raw data for training and evaluation.
- Collaborate with data scientists, software developers, and product teams to integrate models into applications.
- Monitor and maintain the performance of deployed models.
- Stay updated with the latest developments in AI, ML, and data science.
Required Skills:
- Strong understanding of machine learning algorithms and principles.
- Experience with Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, Keras, etc.
- Familiarity with data processing tools like Pandas, NumPy, etc.
- Basic knowledge of deep learning and neural networks.
- Experience with data visualization tools (e.g., Matplotlib, Seaborn, Plotly).
- Knowledge of model evaluation and optimization techniques.
- Familiarity with version control (Git), Jupyter Notebooks, and cloud environments (AWS, GCP, or Azure) is a plus.
Educational Qualification:
- Bachelor's or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
Nice to Have:
- Exposure to NLP, Computer Vision, or Time Series Analysis.
- Experience with ML Ops or deployment pipelines.
- Understanding of REST APIs and integration of ML models with web apps.
Why Join Us:
- Work on real-time AI & ML projects.
- Opportunity to learn and grow in a fast-paced, innovative environment.
- Friendly and collaborative team culture.
- Career development support and training.
Description
Job Summary
We are seeking a visionary Senior AI Engineer with a minimum of 3+ years of experience to lead the development of an advanced AI system leveraging CrewAI and LangChain tools to build intelligent, collaborative multi-agent systems for the logistics domain. The role includes designing AI agents capable of handling complex tasks, optimizing workflows, and conducting A/B and beta testing to ensure robust, scalable performance under diverse conditions. This is an opportunity to shape cutting-edge AI systems and revolutionize logistics operations.
Responsibilities:
1. Design & Architecture:
Architect and implement a multi-agent AI system using CrewAI for task collaboration, communication, and real-time logistics optimization.
Integrate LangChain tools for natural language understanding, contextual reasoning, and knowledge retrieval.
Ensure the system is designed to allow comprehensive testing, iteration, and improvement.
2. AI Agent Development:
Develop autonomous agents capable of dynamic decision-making, task delegation, and seamless inter-agent communication.
Use LangChain to enhance agent capabilities, such as reasoning over unstructured data and interfacing with external knowledge bases.
3. A/B Testing & Experimentation:
Design and execute A/B tests to compare AI agent strategies, workflows, and decision-making models under varying scenarios.
Develop and implement metrics for evaluating system performance (e.g., latency, accuracy, scalability).
Use experimentation frameworks to test hypotheses and gather insights on system improvements.
4. Beta Testing & Real-World Simulation:
Set up controlled beta testing environments that mimic real-world logistics operations.
Simulate edge cases, bottlenecks, and high-load scenarios to ensure system robustness and scalability.
Gather feedback from beta users and iterate on the system to address discovered issues.
5. Progress Demonstration:
Develop dashboards and visualizations to showcase key performance indicators (KPIs) and test results.
Implement tools to log and track agent interactions, decision outcomes, and error rates in real-time.
Regularly present progress to stakeholders, highlighting improvements and areas for refinement.
6. Optimization & Scalability:
Optimize multi-agent interactions and resource allocation for real-world logistics challenges.
Ensure the system scales seamlessly for complex operations involving high volumes of agents and data.
7. Integration:
Seamlessly integrate the multi-agent system with logistics platforms, such as Transportation Management Systems (TMS) and Warehouse Management Systems (WMS).
Use LangChain tools to connect agents to APIs, external knowledge graphs, and live data streams.
8. Collaboration & Leadership:
Lead a team of engineers in developing advanced AI solutions, mentoring them on testing frameworks and innovative technologies like CrewAI and LangChain.
Collaborate with cross-functional teams to align AI development with business needs.
9. Research & Innovation:
Stay updated on the latest advancements in multi-agent systems, LangChain, CrewAI, and testing frameworks.
Introduce cutting-edge techniques to continuously improve the AI system’s performance.
Required Qualifications:
Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
Experience:
• 3+ years in AI development, with experience in multi-agent systems, logistics, or related fields.
• Proven experience in conducting A/B testing and beta testing for AI systems.
• Hands-on experience with CrewAI and LangChain tools.
• Should have hands-on experience working with end-to-end chatbot development, specifically with Agentic and RAG-based chatbots. It is essential that the candidate has been involved in the entire lifecycle of chatbot creation, from design to deployment.
• Should have practical experience with LLM application deployment.
Technical Skills:
• Proficiency in Python and machine learning frameworks (e.g., TensorFlow, PyTorch).
• Strong understanding of A/B testing platforms and methodologies for AI systems.
• Expertise in building beta testing pipelines and real-world simulation environments.
• Familiarity with distributed systems, reinforcement learning, and natural language processing (NLP).
• Proficiency in using LangChain tools for chaining tasks, knowledge retrieval, and reasoning.
• Proficiency with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).
• Good to have experience in Cursor & MCP.
• Experience in setting up monitoring dashboards with tools like Grafana, Tableau, or similar.
Preferred Qualifications:
Experience in logistics systems, such as route optimization, shipment tracking, and demand forecasting.
Familiarity with graph theory, network optimization, and blockchain for agent security.
Background in designing scalable systems tested under diverse operational conditions.
Soft Skills:
Strong analytical and problem-solving abilities.
Ability to communicate technical concepts effectively to stakeholders.
Leadership skills for mentoring teams and guiding project execution.
Artificial Intelligence Researcher
Job description
This is a full-time on-site role for an Artificial Intelligence Researcher at Daten & Wissen in Mumbai. The researcher will be responsible for conducting cutting-edge research in areas such as Computer Vision, Natural Language Processing, Deep Learning, and Time Series Predictions. The role involves collaborating with industry partners, developing AI solutions, and contributing to the advancement of AI technologies.
Key Responsibilities:
- Design, develop, and implement computer vision algorithms for object detection, tracking, recognition, segmentation, and activity analysis.
- Train and fine-tune deep learning models (CNNs, RNNs, Transformers, etc.) for various video and image-based tasks.
- Work with large-scale datasets and annotated video data to enhance model accuracy and robustness.
- Optimize and deploy models to run efficiently on edge devices, cloud environments, and GPUs.
- Collaborate with cross-functional teams including data scientists, backend engineers, and UI/UX designers.
- Continuously explore new research, tools, and technologies to enhance our product capabilities.
- Perform model evaluation, testing, and benchmarking for accuracy, speed, and reliability.
Required Skills:
- Proficiency in Python and C++.
- Experience with object detection models like YOLO, SSD, Faster R-CNN.
- Strong understanding of classical computer vision techniques (OpenCV, image processing, etc.).
- Expertise in Machine Learning, Pattern Recognition, and Statistics.
- Experience with frameworks like TensorFlow, PyTorch, MXNet.
- Strong understanding of Deep Learning and Video Analytics.
- Experience with CUDA, Docker, Nvidia NGC Containers, and cloud platforms (AWS, Azure, GCP).
- Familiar with Kubernetes, Kafka, and model optimization for Nvidia hardware (e.g., TensorRT).
Qualifications
- 2+ years of hands-on experience in computer vision and deep learning.
- Computer Science and Data Science skills
- Expertise in Pattern Recognition
- Strong background in Research and Statistics
- Proficiency in Machine Learning algorithms
- Experience with AI frameworks such as TensorFlow or PyTorch
- Excellent problem-solving and analytical skills
Location : Mumbai (Bhayandar)
Job Description:
As a Machine Learning Engineer, you will:
- Operationalize AI models for production, ensuring they are scalable, robust, and efficient.
- Work closely with data scientists to optimize machine learning model performance.
- Utilize Docker and Kubernetes for the deployment and management of AI models in a production environment.
- Collaborate with cross-functional teams to integrate AI models into products and services.
Responsibilities:
- Develop and deploy scalable machine learning models into production environments.
- Optimize models for performance and scalability.
- Implement continuous integration and deployment (CI/CD) pipelines for machine learning projects.
- Monitor and maintain model performance in production.
Key Performance Indicators (KPI) For Role:
- Success in deploying scalable and efficient AI models into production.
- Improvement in model performance and scalability post-deployment.
- Efficiency in model deployment and maintenance processes.
- Positive feedback from team members and stakeholders on AI model integration and performance.
- Adherence to best practices in machine learning engineering and deployment.
Prior Experience Required:
- 2-4 years of experience in machine learning or data science, with a focus on deploying machine learning models into production.
- Proficient in Python and familiar with data science libraries and frameworks (e.g., TensorFlow, PyTorch).
- Experience with Docker and Kubernetes for containerization and orchestration of machine learning models.
- Demonstrated ability to optimize machine learning models for performance and scalability.
- Familiarity with machine learning lifecycle management tools and practices.
- Experience in developing and maintaining scalable and robust AI systems.
- Knowledge of best practices in AI model testing, versioning, and deployment.
- Strong understanding of data preprocessing, feature engineering, and model evaluation metrics.
Employer:
RaptorX.ai
Location:
Hyderabad
Collaboration:
The role requires collaboration with data engineers, software developers, and product managers to ensure the seamless integration of AI models into products and services.
Salary:
Competitive, based on experience.
Education:
- Bachelor's degree in Computer Science, Information Technology, or a related field.
Language Skills:
- Strong command of Business English, both verbal and written, is required.
Other Skills Required:
- Strong analytical and problem-solving skills.
- Proficiency in code versioning tools, such as Git.
- Ability to work in a fast-paced and evolving environment.
- Excellent teamwork and communication skills.
- Familiarity with agile development methodologies.
- Understanding of cloud computing services (AWS, Azure, GCP) and their use in deploying machine learning models is a plus.
Other Requirements:
- Proven track record of successfully deploying machine learning models into production.
- Ability to manage multiple projects simultaneously and meet deadlines.
- A portfolio showcasing successful AI/ML projects.
Founders and Leadership
RaptorX is led by seasoned founders with deep expertise in security, AI, and enterprise solutions. Our leadership team has held senior positions at global tech giants like Microsoft, Palo Alto Networks, Akamai, and Zscaler, solving critical problems at scale.
We bring not just technical excellence, but also a relentless passion for innovation and impact.
The Market Opportunity
Fraud costs the global economy trillions of dollars annually, and traditional fraud detection methods simply can't keep up. The demand for intelligent, adaptive solutions like RaptorX is massive and growing exponentially across industries like:
- Fintech and Banking
- E-commerce
- Payments
This is your chance to work on a product that addresses a multi-billion-dollar market with huge growth potential.
The Tech Space at RaptorX
We are solving large-scale, real-world problems using modern technologies, offering specialized growth paths for every tech role.
Why You Should Join Us
- Opportunity to Grow: As an early-stage startup, every contribution you make will have a direct impact on the company’s growth and success. You’ll wear multiple hats, learn fast, and grow exponentially.
- Innovate Every Day: Solve complex, unsolved problems using the latest in AI, Graph Databases, and advanced analytics.
- Collaborate with the Best: Work alongside some of the brightest minds in the industry. Learn from leaders who have built and scaled successful products globally.
- Make an Impact: Help businesses reduce losses, secure customers, and prevent fraud globally. Your work will create a tangible difference.
Role Overview
We are seeking a highly skilled and innovative AI Engineer to join our dynamic team. In this role, you will design, develop, and deploy cutting-edge artificial intelligence (AI) solutions, leveraging advanced machine learning (ML) techniques and AI frameworks to address complex business challenges. You will work closely with cross-functional teams to build intelligent systems and drive innovation, with a focus on implementing and optimizing modern AI technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents.
Key Responsibilities
AI Model Development
- Design, develop, and optimize AI solutions, including LLMs, RAG architectures, and Graph-based RAG systems, tailored to specific business needs.
- Develop and fine-tune models for tasks such as Natural Language Processing (NLP), Computer Vision, and Reinforcement Learning (RL).
Prompt Engineering and AI Agents
- Work with prompt optimization to enhance LLM-based responses for specific use cases.
- Develop autonomous AI agents capable of completing multi-step tasks with minimal human intervention.
Data Processing and Management
- Collect, clean, preprocess, and organize datasets for effective AI and ML model training and evaluation.
- Leverage graph databases and vector stores for efficient data retrieval in AI-driven systems.
Algorithm Selection and Optimization
- Choose and implement appropriate algorithms, considering constraints such as scalability, interpretability, and real-time deployment requirements.
- Conduct hyperparameter tuning and optimization experiments to maximize model efficiency and accuracy.
Deployment and Integration
- Deploy AI/ML models in production-grade environments, ensuring scalability, reliability, and seamless integration with existing systems.
- Implement model monitoring pipelines to ensure performance consistency over time.
Research and Development
- Stay abreast of the latest trends and advancements in AI and ML technologies, such as transformer architectures, diffusion models, and multi-modal AI.
- Experiment with emerging tools like LangChain, Hugging Face, and OpenAI APIs to innovate solutions.
Collaboration and Knowledge Sharing
- Work closely with data scientists, software engineers, and product managers to define project requirements and deliver impactful AI solutions.
- Document workflows, processes, and findings to enable knowledge sharing and continuity across teams.
Required Qualifications
Education
- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, Mathematics, or a related field.
Experience
- Minimum 3+ years in AI/ML roles with a proven track record in building and deploying AI-driven solutions.
Technical Proficiency
- Proficiency in Python and AI/ML frameworks like TensorFlow, PyTorch, scikit-learn, or Keras.
- Experience working with LLMs, transformers, and generative AI tools.
- Familiarity with cloud platforms such as AWS, Google Cloud, or Azure, including AI-focused services like SageMaker and Vertex AI.
- Knowledge of vector databases (e.g., Pinecone, Milvus, Weaviate) and graph databases for RAG systems.
Analytical Expertise
- Strong understanding of advanced statistical methods, mathematical concepts, and probabilistic models.
- Ability to analyze and interpret data for actionable insights and model improvements.
Soft Skills
- Exceptional problem-solving and critical-thinking abilities.
- Strong communication skills to effectively collaborate with cross-functional teams.
- Adaptability to a fast-paced, innovation-driven environment.
Preferred Qualifications
- Hands-on experience with LangChain, Hugging Face Transformers, or OpenAI API integrations.
- Expertise in specialized AI domains like multi-modal learning, conversational AI, and prompt engineering.
- Contributions to open-source AI projects or publications in recognized AI/ML conferences or journals.
- Familiarity with deploying AI Agents in production systems.
What We Offer
- Competitive Compensation & Benefits aligned with your experience and the impact you bring.
- Opportunity for Growth in a rapidly expanding B2B SaaS company.
- Cutting-Edge Technology & Projects in the WhatsApp Business API and Click to WhatsApp Ads space.
- Collaborative Work Environment that fosters innovation, learning, and career development.
- Flexible & Inclusive Culture, where every team member has a voice and the chance to make a significant impact.
JioTesseract, a digital arm of Reliance Industries, is India's leading and largest AR/VR organization with the mission to democratize mixed reality for India and the world. We make products at the cross of hardware, software, content and services with focus on making India the leader in spatial computing. We specialize in creating solutions in AR, VR and AI, with some of our notable products such as JioGlass, JioDive, 360 Streaming, Metaverse, AR/VR headsets for consumers and enterprise space.
Mon-fri role, In office, with excellent perks and benefits!
Position Overview
We are seeking a Software Architect to lead the design and development of high-performance robotics and AI software stacks utilizing NVIDIA technologies. This role will focus on defining scalable, modular, and efficient architectures for robot perception, planning, simulation, and embedded AI applications. You will collaborate with cross-functional teams to build next-generation autonomous systems 9
Key Responsibilities:
1. System Architecture & Design
● Define scalable software architectures for robotics perception, navigation, and AI-driven decision-making.
● Design modular and reusable frameworks that leverage NVIDIA’s Jetson, Isaac ROS, Omniverse, and CUDA ecosystems.
● Establish best practices for real-time computing, GPU acceleration, and edge AI inference.
2. Perception & AI Integration
● Architect sensor fusion pipelines using LIDAR, cameras, IMUs, and radar with DeepStream, TensorRT, and ROS2.
● Optimize computer vision, SLAM, and deep learning models for edge deployment on Jetson Orin and Xavier.
● Ensure efficient GPU-accelerated AI inference for real-time robotics applications.
3. Embedded & Real-Time Systems
● Design high-performance embedded software stacks for real-time robotic control and autonomy.
● Utilize NVIDIA CUDA, cuDNN, and TensorRT to accelerate AI model execution on Jetson platforms.
● Develop robust middleware frameworks to support real-time robotics applications in ROS2 and Isaac SDK.
4. Robotics Simulation & Digital Twins
● Define architectures for robotic simulation environments using NVIDIA Isaac Sim & Omniverse.
● Leverage synthetic data generation (Omniverse Replicator) for training AI models.
● Optimize sim-to-real transfer learning for AI-driven robotic behaviors.
5. Navigation & Motion Planning
● Architect GPU-accelerated motion planning and SLAM pipelines for autonomous robots.
● Optimize path planning, localization, and multi-agent coordination using Isaac ROS Navigation.
● Implement reinforcement learning-based policies using Isaac Gym.
6. Performance Optimization & Scalability
● Ensure low-latency AI inference and real-time execution of robotics applications.
● Optimize CUDA kernels and parallel processing pipelines for NVIDIA hardware.
● Develop benchmarking and profiling tools to measure software performance on edge AI devices.
Required Qualifications:
● Master’s or Ph.D. in Computer Science, Robotics, AI, or Embedded Systems.
● Extensive experience (7+ years) in software development, with at least 3-5 years focused on architecture and system design, especially for robotics or embedded systems.
● Expertise in CUDA, TensorRT, DeepStream, PyTorch, TensorFlow, and ROS2.
● Experience in NVIDIA Jetson platforms, Isaac SDK, and GPU-accelerated AI.
● Proficiency in programming languages such as C++, Python, or similar, with deep understanding of low-level and high-level design principles.
● Strong background in robotic perception, planning, and real-time control.
● Experience with cloud-edge AI deployment and scalable architectures.
Preferred Qualifications
● Hands-on experience with NVIDIA DRIVE, NVIDIA Omniverse, and Isaac Gym
● Knowledge of robot kinematics, control systems, and reinforcement learning
● Expertise in distributed computing, containerization (Docker), and cloud robotics
● Familiarity with automotive, industrial automation, or warehouse robotics
● Experience designing architectures for autonomous systems or multi-robot systems.
● Familiarity with cloud-based solutions, edge computing, or distributed computing for robotics
● Experience with microservices or service-oriented architecture (SOA)
● Knowledge of machine learning and AI integration within robotic systems
● Knowledge of testing on edge devices with HIL and simulations (Isaac Sim, Gazebo, V-REP etc.)

























