AI ML Engineer at Aaizel International Technologies Pvt Ltd · Gurugram · 4 - 8 years · ₹6L - ₹10L / yr · Raised funding · Posted 25 Jul 2026

AI ML Engineer
Job Title: Associate AI/ML Engineer
Location: Gurugram, Haryana
Employment Type: Full-Time
About Aaizel Tech
Aaizel Tech is a pioneering tech startup at the intersection of cybersecurity, AI, geospatial solutions, and more. We drive innovation by delivering transformative technology solutions across industries. As a growing startup, we are looking for passionate and versatile professionals eager to work on cutting-edge projects in a dynamic environment.
Role Overview
As a Associate AI/ML Engineer at Aaizel Tech, you will lead the design, development, and deployment of advanced Machine Learning models and AI solutions. You will work on projects ranging from predictive analytics and NLP to computer vision and anomaly detection. You will also mentor a team of AI/ML professionals, collaborate with cross-functional teams, and drive innovation by integrating state-of-the-art research with scalable production systems.
Key Responsibilities
1. Model Development & Optimization
Design & Implementation:
- Architect and develop end-to-end ML solutions for applications such as predictive analytics, anomaly detection, computer vision, and NLP.
- Utilize advanced techniques including deep learning (CNNs, RNNs), reinforcement learning, and generative models (GANs) to address complex challenges.
Optimization:
- Fine-tune model parameters using techniques such as hyperparameter tuning (Grid Search, Bayesian Optimization, Neural Architecture Search).
- Optimize models for both accuracy and inference speed to meet real-time processing requirements.
2. Advanced Data Engineering & Integration
Data Pipeline Development:
- Build robust ETL pipelines using libraries like Pandas, NumPy, and PySpark to process large-scale datasets from satellite imagery, IoT sensors, and real-time streams.
- Integrate data from diverse sources (APIs, databases, big data platforms like Hadoop and Apache Kafka) to support real-time analytics.
Data Quality & Preprocessing:
- Implement data cleansing, feature engineering, and transformation pipelines to ensure high-quality inputs for ML models.
3. Research & Innovation
Algorithm Research:
- Conduct research on state-of-the-art ML techniques including Transfer Learning, Transformer models, and AutoML to enhance model performance.
- Innovate new algorithms for specialized tasks such as geospatial analysis, environmental modeling, or cybersecurity threat detection.
Prototyping & Experimentation:
- Develop proof-of-concept models and prototypes to validate new approaches before production deployment.
4. Deployment, MLOps & Performance Monitoring
Model Deployment:
- Deploy models using containerization (Docker) and orchestration tools (Kubernetes) to ensure scalable and efficient production environments.
- Work with cloud platforms (AWS, Azure, GCP) and model serving solutions (TensorFlow Serving, ONNX, TorchServe) for high-throughput inference.
MLOps & Lifecycle Management:
- Implement CI/CD pipelines for ML models, ensuring seamless updates and versioning.
- Develop monitoring dashboards (using Prometheus, Grafana) to track model performance and trigger retraining based on real-time feedback.
5. Collaboration & Leadership
Cross-Functional Teamwork:
- Collaborate closely with data engineers, software developers, domain experts, and product managers to integrate AI solutions into end-to-end products.
Mentorship & Code Quality:
- Provide technical leadership and mentorship to junior AI/ML engineers, ensuring adherence to coding standards and best practices.
- Participate in code reviews, maintain detailed documentation, and foster a culture of continuous learning.
Recommended Technology Stack
Backend Framework:
- Python (Django/FastAPI): Ideal for API integration, leveraging Python’s rich AI/ML ecosystem.
AI/ML Frameworks:
- PyTorch + Hugging Face Transformers + scikit-learn: For flexibility in research, multilingual NLP tasks, and classical ML pipelines.
Data Engineering:
- Apache Kafka + Apache Spark + Apache NiFi: To handle both real-time data streaming and batch processing.
Database & Storage:
- PostgreSQL with TimescaleDB extension: For structured and time-series data storage.
DevOps & Monitoring:
- Docker, Kubernetes, GitLab CI/CD, Prometheus/Grafana: For containerized deployments, continuous integration, and comprehensive monitoring.
Media Processing:
- OpenCV, FFmpeg, Tesseract OCR, Wav2Vec2: To support image, video, and speech-to-text processing where needed.
Required Skills & Qualifications
Technical Expertise:
- Experience:
- 5+ years in Machine Learning, AI research, or a related field with a proven track record of delivering production-level AI solutions.
- Programming & Frameworks:
- Expertise in Python and hands-on experience with frameworks like PyTorch, TensorFlow, and scikit-learn.
- Experience with Hugging Face Transformers for NLP applications.
- Data Engineering:
- Proficiency in building data pipelines using Pandas, NumPy, PySpark, and integrating data from diverse sources.
- Familiarity with big data platforms and real-time data processing frameworks.
- Model Deployment & MLOps:
- Hands-on experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for ML models.
- Experience with cloud deployment and model serving solutions.
- Research & Innovation:
- Demonstrated ability to apply advanced ML techniques (deep learning, transfer learning, reinforcement learning) to solve real-world problems.
- Testing & Optimization:
- Strong background in model evaluation, hyperparameter tuning, and performance optimization.
Soft Skills:
- Exceptional problem-solving and analytical abilities.
- Strong communication skills, with the ability to present complex technical concepts to diverse stakeholders.
- Leadership and mentoring experience, with a collaborative approach to working in cross-functional teams.
- Ability to thrive in a fast-paced, dynamic environment and drive continuous innovation.
Educational Background:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field from a reputed institution.
What We Offer
- Innovative Projects: Engage in cutting-edge AI/ML projects that influence product strategy and technological innovation.
- Professional Growth: Opportunities for continuous learning, mentorship, and career advancement.
- Collaborative Culture: Work within a diverse team of experts passionate about pushing the boundaries of technology.
- Impactful Work: Play a key role in shaping AI-driven solutions and driving real-world impact.

About Aaizel International Technologies Pvt Ltd
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• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.
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• Knowledge of model interpretability, data annotation, and feature engineering.
• C++ experience for high-performance AI applications.
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About NonStop io Technologies
NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.
Brief Description:
We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.
Responsibilities
● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI
● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.
● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data
● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics
● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics
● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems
● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes
● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions
● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.
Qualifications & Skills
● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus
● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects
● Proficiency in programming languages commonly used for AI/ML. Preferably Python
● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.
● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.
● Strong understanding of machine learning algorithms, statistics, and data structures
● Experience with data preprocessing, data wrangling, and feature engineering
● Knowledge of deep learning architectures, neural networks, and transfer learning
● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment
● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code
● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions
● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders
AuxoAI is hiring a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems — including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.
Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)
Responsibilities:
- Own the full ML lifecycle: model design, training, evaluation, deployment
- Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection
- Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines
- Build agentic workflows for reasoning, planning, and decision-making
- Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark
- Leverage state-of-the-art architectures: transformers, diffusion models, RLHF, and multimodal pipelines
- Collaborate with product and engineering teams to integrate AI models into business applications
- Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices
Requirements
- 5+ years of experience in designing, deploying, and scaling ML/DL systems in production
- Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
- Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines
- Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)
- Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows
- Strong software engineering background with experience in testing, version control, and APIs
- Proven ability to balance innovation with scalable deployment
- B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field
- Bonus: Open-source contributions, GenAI research, or applied systems at scale
Key Responsibilities:
- Develop and deploy machine learning, deep learning, and NLP models for various business use cases.
- Build end-to-end ML pipelines including data preprocessing, feature engineering, training, evaluation, and production deployment.
- Optimize model performance and ensure scalability in production environments.
- Work closely with data scientists, product teams, and engineers to translate business requirements into AI solutions.
- Conduct data analysis to identify trends and insights.
- Implement MLOps practices for versioning, monitoring, and automating ML workflows.
- Research and evaluate new AI/ML techniques, tools, and frameworks.
- Document system architecture, model design, and development processes.
Required Skills:
- Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras).
- Hands-on experience in building and deploying, finetuning ML/DL models in production.
- Good understanding of machine learning algorithms, neural networks, NLP, and computer vision.
- Experience with REST APIs, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).
- Working knowledge of MLOps tools such as MLflow, Airflow, DVC, or Kubeflow.
- Familiarity with data pipelines and big data technologies (Spark, Hadoop) is a plus.
- Strong analytical skills and ability to work with large datasets.
- Excellent communication and problem-solving abilities.
- Experience in deploying models using cloud services (AWS Sagemaker, GCP Vertex AI, etc.).
- Experience in LLM fine-tuning or Generative AI, Voice AI, is an added advantage.
Educational Qualification:
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, IT, from IIT/NIT colleges strongly preferred
Kody Technolab Limited
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Location: Ahmedabad / Gandhinagar
Experience: 7+ Years
Employment Type: Full-Time
Kody Technolab Limited is seeking an experienced AI/ML Engineer to design, develop, and deploy
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strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, and
cloud-based AI deployments.
Key Responsibilities
• Design, develop, and deploy Machine Learning and Deep Learning models for classification,
regression, recommendation systems, NLP, Computer Vision, and Generative AI applications.
• Build and maintain end-to-end ML pipelines including data preprocessing, feature
engineering, model training, validation, evaluation, and deployment.
• Develop AI solutions using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and related
frameworks.
• Work with Large Language Models (LLMs) and foundation models such as GPT, BERT, Llama,
Claude, and Stable Diffusion.
• Collaborate with product, engineering, and business teams to translate requirements into
scalable AI solutions.
• Optimize model performance, scalability, and reliability for production environments.
• Implement MLOps best practices using tools such as MLflow, Docker, Kubernetes, and Kubeflow.
• Stay updated with emerging trends and research in AI, ML, Deep Learning, and Generative AI.
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence,
Mathematics, or a related field.
• 7+ years of hands-on experience in AI/ML product development.
• Strong proficiency in Python and ML frameworks including Scikit-learn, TensorFlow, PyTorch, and
Hugging Face.
• Experience with Generative AI, LLMs, GANs, VAEs, diffusion models, and prompt engineering.
• Strong understanding of the ML lifecycle including model training, tuning, deployment,
monitoring, and optimization.
• Experience with MLOps tools such as MLflow, Docker, Kubeflow, and CI/CD pipelines.
• Experience with AWS, Azure, or GCP cloud platforms.
• Strong problem-solving and analytical skills.Preferred Skills
• Fine-tuning and deployment of Large Language Models.
• Experience with RAG (Retrieval Augmented Generation) architectures.
• Contributions to open-source AI projects or research publications.
• Knowledge of model interpretability, data annotation, and feature engineering.
• C++ experience for high-performance AI applications.
Why Join Kody Technolab Limited?
Opportunity to work on innovative AI products, Generative AI solutions, robotics integrations,
and enterprise-scale applications while collaborating with a highly skilled technology team.
Visit the Website to know more about us.
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This is a remote position.
About Leegality:
Leegality works with large Indian businesses to digitally transform critical compliance processes in a fast, easy and secure way.
We have multiple products across 2 categories:
Document Infrastructure:
Products that help businesses build paperless processes at scale:
- Document Execution Workflow: A unified platform for businesses to digitally execute (eSign, eStamp, Template Pre-fill, Document Fraud Prevention etc.) agreements, forms and other documents in a compliant way. Currently in use by 2000+ Indian businesses from giants like HDFC and SBI Cards to high-growth disruptors like goDigit and Cars24.
- Contract Management: An AI-powered platform for businesses to quickly review, negotiate and take action on contract
- Signstation: A simple platform for businesses to digitally sign simple documents like invoices, policies and letters in a cost effective manner
Consent Infrastructure:
- Consentin: An end-to-end DPDP and Privacy compliance platform for Indian businesses
- Consentin Lens: A data discovery platform for businesses to identify the personal data they collect and store.
If you’re interested in building mission critical software that operates at population scale (75 million + Indians have signed at least one document through Leegality) then join Leegality.
Curious about our impact? Explore our customer success stories: leegality.com/case-studies
Our Culture
At Leegality, trust, ownership, transparency, and having fun while doing meaningful work are core to how we operate — not just values on paper. Our team rated us an incredible 97 eNPS for FY 2023–24 — the highest among 175+ startups surveyed.
We focus deeply on helping our people grow and stay motivated. Some of the perks you’ll enjoy:
- Flexible working hours
- Hybrid work setup
- Bi-annual performance appraisals
- A culture that rewards initiative, curiosity, and impact
If you're looking for a place where you can make a real difference while working with smart, driven, and genuinely nice people, welcome to Leegality.
Location: Hybrid
Job Brief:
- As a Machine Learning Engineer specializing in Computer Vision (CV) and Natural Language Processing (NLP), you will develop solutions to interesting technical problems, exploring exciting growth opportunities and having a real impact on our product, particularly focusing on document and content intelligence.
- To ensure success, you should demonstrate solid data science knowledge and experience in a related ML, CV, or NLP role. A first-class engineer will be someone whose expertise enhances our systems for document intelligence and content processing
Responsibilities:
- Designing machine learning systems, self-running artificial intelligence (AI) software, and specialized models for Computer Vision and Natural Language Processing applications.
- Transforming data science prototypes and applying appropriate deep learning algorithms and tools to text and image/document data.
- Solving complex CV and NLP problems with multi-layered data types, such as image/document classification, information extraction, semantic search, and object detection.
- Optimizing existing machine learning models, with a focus on high-performance model deployment for CV and NLP tasks.
- Developing ML algorithms (including large language models/LLMs and computer vision models) to analyze huge volumes of historical text, image, and document data to make predictions and automate workflows.
- Running tests, performing statistical analysis, and interpreting test results for CV/NLP model performance.
- Documenting machine learning processes, model architectures, and data pipelines.
- Keeping abreast of developments in machine learning, Computer Vision, and Natural Language Processing.
Requirements:
- 3+ years of relevant experience in Machine Learning Engineering, with a strong focus on Computer Vision and/or Natural Language Processing.
- Advanced proficiency with Python.
- Extensive knowledge of ML frameworks, libraries (e.g., PyTorch, Transformers), data structures, data modeling, and software architecture.
- Experience with building and maintaining scalable RESTful APIs (e.g., FastAPI).
- In-depth knowledge of mathematics, statistics, deep learning (CNNs, RNNs, Transformers), and algorithms.
- Superb analytical and problem-solving abilities, especially for unstructured data challenges.
- Great communication and collaboration skills.
- Excellent time management and organizational abilities.
- Experience with cloud platforms (e.g., AWS) for model deployment and MLOps.
Recruitment Process:
- Our hiring process combines AI-powered evaluations with structured interviews to ensure a fair and seamless experience.
- You will be contacted via email with the next steps upon being shortlisted.
- The process may include Assessments, AI-enabled interviews, and In-Person Interviews with our team.
- Final selection and CTC will be based on your overall performance and experience.
Apply directly through our career page: https://careers.leegality.com/jobs/Careers
For more information about us please visit our:
Our Company and Culture: https://bit.ly/3Iqm5SB
Our Website: www.leegality.com/
Our LinkedIn Page: www.linkedin.com/company/leegality/
Leegality's Privacy Notice: https://www.leegality.com/employee-privacy-notice
Job Title: Senior AI/ML Engineer
Company: Timble Technologies Pvt. Ltd
Location: Gurugram (Hybrid)
Experience: 2 TO 5 Years
About Us
Timble Glance is a high-growth AI RegTech and B2B SaaS company catering to top-tier BFSI and enterprise clients. We build cutting-edge systems powering 30+ high-scale APIs for digital identity verification, fraud detection, document intelligence, and compliance automation.
Role Overview
We are looking for a hands-on Senior AI/ML Engineer to design, develop, and productionize high-throughput AI/ML and Generative AI systems. You will own the full lifecycle—from problem formulation and data pipelines to deep learning architectures, RAG systems, LLMOps, and model governance—delivering sub-second latency and high reliability across our enterprise products.
Key Responsibilities
· Model Architecture & Deployment: Design, train, and deploy production-scale ML/Deep Learning and GenAI systems (computer vision, document intelligence, OCR, NLP, fraud risk classification, and LLM applications).
· GenAI & LLM Solutions: Develop robust LLM workflows including prompt engineering, fine-tuning, RAG pipelines, semantic search, vector indexing (Pinecone/Milvus/Chroma), and safety guardrails.
· Pipelines & Engineering: Build performant feature extraction and data pipelines; write modular, vectorized, production-grade Python (NumPy, Pandas) and advanced SQL.
· MLOps & Monitoring: Establish end-to-end MLOps/LLMOps standards—model registries, CI/CD, experiment tracking, drift detection, A/B testing, latency optimization, and cost governance.
· Responsible AI & Security: Ensure model decisions comply with enterprise data security, privacy standards, and auditability required by the BFSI sector.
· Collaboration & Ownership: Translate complex business requirements into technical roadmaps, conduct rigorous code reviews, and mentor junior engineers.
Required Qualifications & Skills
· Education: B.Tech / M.Tech in Computer Science, AI/ML, Mathematics, or a related field—Tier-1 institutes (IIT, IIIT, NIT) strongly preferred.
· Experience: 2+ years of hands-on experience developing, deploying, and maintaining ML/Deep Learning or GenAI models in production environments.
· GenAI & NLP Stack: Hands-on experience with LLMs, embeddings, RAG architectures, and frameworks such as LangChain, LlamaIndex, or Hugging Face.
· Deep Learning Frameworks: Strong proficiency in PyTorch or TensorFlow, with deep knowledge of transformer architectures and modern NLP/CV models.
· Software & Data Engineering: Expert-level Python skills (pytest, Git, OOP, asynchronous programming), solid SQL proficiency, and familiarity with data workflows.
· Deployment & Cloud: Practical exposure to cloud platforms (AWS/GCP), containerization (Docker), API frameworks (FastAPI/Flask), and basic orchestration (Kubernetes).
Preferred Qualifications
· Prior domain experience in Fintech, RegTech, Identity Verification (KYC/AML), Fraud Intelligence, or B2B SaaS.
· Experience optimizing models for low latency and inference cost (e.g., ONNX, TensorRT, model quantization).
· Familiarity with workflow orchestrators such as Airflow, Prefect, or Kubeflow.
ML DEVELOPER
Hyperworks Imaging is a cutting-edge technology company based out of Bengaluru, India since 2016. Our team uses the latest advances in deep learning and multi-modal machine learning techniques to solve diverse real world problems. We are rapidly growing, working with multiple companies around the world.
JOB OVERVIEW
We are seeking a talented and results-oriented ML Developer to join our growing team in India. In this role, you will be responsible for developing and implementing new advanced ML algorithms and AI agents for creating AI assistants of the future.
The ideal candidate will work on a complete ML pipeline starting from extraction, transformation and analysis of data to developing novel ML algorithms. The candidate will implement latest research papers and closely work with various stakeholders to ensure data-driven decisions and integrate the solutions into a robust ML pipeline.
RESPONSIBILITIES:
- Create AI agents using Model Context Protocols (MCPs), Claude Code, DsPy etc.
- Develop custom evals for AI agents.
- Build and maintain ML pipelines
- Optimize and evaluate ML models to ensure accuracy and performance.
- Define system requirements and integrate ML algorithms into cloud based workflows.
- Write clean, well-documented, and maintainable code following best practices
REQUIREMENTS:
- 2-3+ years of experience in data science, machine learning, or a similar role.
- Demonstrated expertise with python, PyTorch, and TensorFlow.
- Graduated/Graduating with B.Tech/M.Tech/PhD degrees in Electrical Engg./Electronics Engg./Computer Science/Maths and Computing/Physics
- Has done coursework in Linear Algebra, Probability, Image Processing, Deep Learning and Machine Learning.
- Has demonstrated experience with Model Context Protocols (MCPs), DSPy, AI Agents, MLOps etc
WHO CAN APPLY:
Only those candidates will be considered who,
- have relevant skills and interests
- can commit full time
- Can show prior work and deployed projects
- can start immediately
Please note that we will reach out to ONLY those applicants who satisfy the criteria listed above.
SALARY DETAILS: Commensurate with experience.
JOINING DATE: Immediate
JOB TYPE: Full-time
Role Overview
We are looking for an AI/ML Engineer with 2 - 6 years of industry experience to develop and deploy machine learning solutions for industrial and smart manufacturing use cases. The role involves working with real-world industrial data, developing predictive and analytical models, and translating business and operational requirements into scalable AI/ML solutions.
The ideal candidate should have strong fundamentals in machine learning, Python, data processing, model development, and deployment, along with an interest in applying AI to manufacturing, industrial automation, and operational optimization.
Key Responsibilities
- Design, develop, train, and evaluate machine learning models for industrial and manufacturing use cases.
- Analyze large and complex datasets to identify patterns, trends, anomalies, and opportunities for optimization.
- Perform data preprocessing, feature engineering, model selection, and performance evaluation.
- Develop solutions for use cases such as predictive maintenance, anomaly detection, quality prediction, process optimization, forecasting, and equipment monitoring.
- Work with structured and time-series data generated from industrial equipment, machines, sensors, and operational systems.
- Develop and optimize ML pipelines for data preparation, model training, validation, and deployment.
- Collaborate with domain experts, data engineers, software engineers, and business stakeholders to understand requirements and translate them into technical solutions.
- Deploy machine learning models into production environments and monitor model performance.
- Troubleshoot model and data-related issues and continuously improve model accuracy, reliability, and scalability.
- Develop reusable code, APIs, and components to integrate ML models with enterprise and industrial applications.
- Document models, methodologies, experiments, results, and technical implementations.
- Stay updated with emerging AI/ML techniques, industrial AI trends, and smart manufacturing technologies.
Required Technical Skills
- Strong programming experience in Python.
- Good understanding of Machine Learning algorithms and concepts.
- Experience with libraries/frameworks such as Scikit-learn, Pandas, NumPy, and preferably TensorFlow or PyTorch.
- Strong understanding of data preprocessing, feature engineering, model training, validation, and evaluation.
- Experience working with time-series data is preferred.
- Good understanding of statistical concepts and data analysis.
- Experience with SQL and relational databases.
- Understanding of model deployment and productionization of ML solutions.
- Familiarity with Git and software development best practices.
- Good problem-solving and analytical skills.
Preferred Skills
- Experience in Industrial AI, Smart Manufacturing, Industry 4.0, or Industrial IoT (IIoT).
- Experience with predictive maintenance, anomaly detection, forecasting, or quality inspection.
- Exposure to sensor data, machine/equipment data, telemetry, or real-time industrial data.
- Knowledge of computer vision for manufacturing or quality inspection use cases.
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Familiarity with Docker, Kubernetes, or CI/CD for ML deployment.
- Knowledge of MLOps concepts and tools.
- Exposure to Generative AI/LLMs is an added advantage.
Strong AI/ML Engineer Profile
Mandatory (Experience) : Must have 3+ years of experience in software engineering with atleast 1+ years in GenAI application development and production deployment
Mandatory (GenAI Application Development): Must have proven experience building GenAI applications covering RAG pipelines, multi-agent systems, Text2SQL, and fine-tuning
Mandatory (Production GenAI Deployment): Must have expertise deploying production-grade GenAI applications including model evaluation, optimisation, and ownership of full production rollouts
Mandatory (ML & Data Science Tooling): Must have strong hands-on experience with core ML and data science tools including pandas, scikit-learn, and PyTorch
Mandatory (Cloud ML Infrastructure): Must have experience building and deploying production-grade ML workloads on at least one of AWS, Azure, or GCP
Mandatory (Communication): Must have strong English communication skills with the ability to work across time zones and collaborate cross-functionally with product, engineering, and business stakeholders
Mandatory (Note 1) : Role is Hybrid, WFH flexibility as well upto 6 days a month
Mandatory (Note 2) : CTC is inclusive of 10% variable
Mandatory (Note 3): Candidates should be available to join within May 31st or June first week max












