Lead Data Scientist at Agritech ||Gurgaon · Gurugram · 2 - 6 years · ₹18L - ₹35L / yr · Posted 6 Dec 2022

- Architecting end-to-end prediction pipelines and managing them
- Scoping projects and mentoring 2-4 people
- Owning parts of the AI and data infrastructure of the organization
- Develop state-of-the-art deep learning/classical models
- Continuously learn new skills and technologies and implement them when relevant
- Contribute to the community through open-source, blogs, etc.
- Take a number of high-quality decisions about infrastructure, pipelines, and internal tooling.
What are we looking for
- Deep understanding of core concepts
- Broader knowledge of different types of problem statements and approaches
- Great hold on Python and the standard library
- Knowledge of industry-standard tools like scikit-learn, TensorFlow/PyTorch, etc.
- Experience with at least one among Computer Vision, Forecasting, NLP, or Recommendation
Systems a must
- A get shit done attitude
- A research mindset and a creative caliber to utilize previous work to your advantage.
- A helping/mentoring first approach towards work

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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
Kody Technolab Limited is seeking an experienced AI/ML Engineer to design, develop, and deploy cutting-edge Artificial Intelligence and Machine Learning solutions. The ideal candidate will have
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.
Company Website - Kody Technolab | Deep Tech Company in Robotics & AI Solution
Kody Robots | Robotics Company in India for Autonomous Robots
About the Role
We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.
Key Responsibilities
· Design, develop, and deploy machine learning models for real-world business problems
· Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring
· Implement and manage MLOps pipelines for scalable and reproducible workflows
· Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management
· Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications
· Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions
· Optimize model performance and ensure production stability
· Stay updated with the latest advancements in AI/ML and GenAI ecosystems
Required Skills & Qualifications
· 4+ years of experience in Data Science / Machine Learning
· Strong programming skills in Python
· Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)
· Solid understanding of MLOps practices and tools
· Experience with MLflow or similar model lifecycle tools
· Practical experience in Generative AI (GenAI), including working with LLMs
· Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch
· Strong understanding of data structures, algorithms, and statistics
· Experience with cloud platforms (AWS/GCP/Azure) is a plus
Good to Have
· Experience with LLM fine-tuning, prompt engineering, or RAG pipelines
· Exposure to Docker, Kubernetes, and CI/CD pipelines
· Knowledge of data engineering workflows
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
AI/ML Engineer AI Operating System for Capital Markets Location Bangalore/Chennai Experience 5+ years Function Artificial Intelligence / Machine Learning Employment Type About Transient.AI Full-time Transient.AI is building a next-generation AI Operating System for capital markets — a unified intelligence layer that connects research, trading, compliance, and sales functions at banks and hedge funds. Today, these teams largely operate on disconnected legacy systems, forcing manual, expensive workarounds. Transient.AI replaces that fragmentation with a single AI-native layer built for institutional-grade compliance, security, and auditability. The company already has live products in market, including Caddie.AI (a research automation tool that cuts hedge fund research time significantly), ClarityRIA (helping sales teams identify the right investors in seconds), and CapFlo.AI (automated parsing of complex derivatives contracts). Founded by former traders and technologists from Goldman Sachs, Credit Suisse, UBS, and McKinsey, Transient.AI is headquartered in New York, with teams in Miami, Singapore, and India. The company has raised Series A funding and is scaling its engineering and product organization globally. Role Overview Transient.AI is hiring an experienced AI/ML Engineer to join its India engineering team in Bangalore/Chennai. This is a hands-on, build-from-scratch role — you'll be designing and shipping the core machine learning systems that power the company's flagship products, working closely with founders and senior engineers rather than inheriting existing infrastructure. Key Responsibilities • Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research automation, document intelligence, investor matching, and workflow orchestration). • Workonapplied NLP/LLMsystems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines. • Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems. • Ownmodelperformance, reliability, and cost — from experimentation through production deployment. • Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration. • Ensuresystems meet the compliance, auditability, and security standards required in regulated financial environments. What We're Looking For • 5+years ofexperience building and deploying machine learning or AI systems in production.• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent). • Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly valued. • Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning). • Prior experience at a strong product company, high-growth startup, or a top-tier engineering background • Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity. • Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory. WhyJoin Transient.AI • Build core AI systems from the ground up — not maintain legacy code. • Workdirectly with founders who have deep, first-hand Wall Street experience (Goldman Sachs, Credit Suisse, UBS, McKinsey). • JoinaSeries A-funded company solving a real, expensive problem for institutional finance. • Bepart ofasmall, global team with outsized ownership and impact. .
Sr.Data Scientist,Python, AI ML
We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.
- We are looking for experienced AI/ML Architects to join our AI Engineering service line. In this role, you will anchor the technical delivery of enterprise AI/Agentic AI projects post deal-closure. You will take over from solution architects and lead the design, build, deployment, and optimization of AI/ML systems — ensuring production-grade quality, scalability, and compliance.
- You will interface with cross-functional teams, manage engineering complexity, and ensure value realization for customers across industries such as BFSI, HLS, Manufacturing, CMT, Retail, and Energy.
Key Responsibilities
Architecture & Technical Leadership
Hands-on Engineering & Problem Solving
Required Qualifications
Education : B.Tech/M.Tech or equivalent in Computer Science, Data Science, or a related field.
Experience
● 10+ years in software architecture or engineering with 5+ years in applied AI/ML
system delivery.
● Experience in productionizing AI/ML models and building full-stack AI applications in
enterprise settings.
● Strong Python development skills; proficiency in ML/AI frameworks (PyTorch,
TensorFlow, Scikit-learn).
● Strong understanding of LLMs, RAG pipelines, vector databases (Weaviate, Qdrant,
Pinecone).
● Experience with MLOps/LLMOps tools: MLflow, Argo, KServe, Feast, Kubeflow.
● Proficiency in data pipeline engineering using Spark, Airflow, or DataFlow.
● Exposure to agent orchestration frameworks: LangChain, LangGraph, AutoGen,
CrewAI is a big plus.
● Cloud & Infrastructure
● Hands-on experience with GCP (Vertex AI, BigQuery, Document AI, AI Gateway)
and/or Azure (Azure ML, OpenAI, Synapse).
● Expertise in containerization (Docker) and orchestration (Kubernetes).
● Familiarity with Infrastructure as Code (Terraform, Pulumi, CDK).
Soft Skills
Strong architectural thinking and problem-solving in fast-paced delivery environments.
Excellent communication and collaboration skills to work across cross-functional teams and
clients.
Proactive, structured, and detail-oriented with a bias for execution.
Nice to Have
Experience in real-world deployments of Agentic AI systems or collaborative multi-agent setups.
Exposure to regulatory/ethical concerns in AI such as fairness, transparency, or bias mitigation.
Familiarity with AI observability, explainability, and governance tooling (e.g., Arize, Fiddler,
TruEra).
Description
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 strong talent and compensate accordingly.
- Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
- Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
- High-impact work: Build AI-first systems and products used at scale by global clients.
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 built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Strong AI Engineer / Machine Learning Engineer profiles.
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Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
3
Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
4
Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
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Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.
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Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
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Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.
8
Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
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Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
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Mandatory (Age) - Candidate's Age should be below 30 Years
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Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.
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Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..
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Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.
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Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies
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Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.
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.






