Data Scientist (Gen/Agentic AI solutions)
Senior data scientist at building-materials company Holcim building its internal GenAI/agentic AI platform: RAG infrastructure, LLM evaluation pipelines, agentic orchestration, and MLOps/LLMOps tooling. Day to day involves Python, Databricks/AWS, vector databases, and LLM APIs (OpenAI, Anthropic, etc.).
- Compensation
- Not disclosed
- Location
- Navi Mumbai, MH, IN, 400708
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data science
- Posted
Skills
Must have
- BE / B.Tech in Computer Science, Engineering or relevant field
- Strong mathematics skills (statistics, algebra)
- Certification in Gen/Agentic AI solutions
- 8+ years progressive experience in data science and ML, min 3 years in Generative AI / LLM-based systems
- Track record delivering AI solutions at enterprise scale
- Hands-on full AI/ML lifecycle: data engineering, feature stores, training, evaluation, deployment, monitoring
- Proficiency in Python with LangChain, LangGraph, HuggingFace Transformers, PyTorch, scikit-learn, Pandas, NumPy
- Deep experience with LLM APIs (OpenAI, Anthropic, Google, Mistral) and open-source deployment via Ollama, vLLM, TGI
- Vector databases, semantic search, knowledge graphs for enterprise RAG architectures
- MLOps tooling: MLflow, Weights & Biases, Kubeflow; LLMOps tools like LangSmith
- Strong SQL and modern data platforms such as Databricks
- Software engineering best practices: Git, Docker/Kubernetes, REST/gRPC API design, CI/CD
- Benchmarking GenAI models beyond accuracy (toxicity, bias, reasoning depth)
- Exposure to multi-modal AI systems (vision, audio, document understanding)
- Understanding of GenAI standards (MCP, A2A, A2UI)
- Result-oriented with a work ethic of delivering on-time and in scope
Nice to have
- Graduate degree in Data Science or other quantitative field
- Certification in Databricks, AWS platforms
- Industry experience in Manufacturing / Building Materials / Process or Pharma
Full description
About The RoleQualifications:
-
BE / B. Tech in Computer Science, Engineering or relevant field
-
Graduate degree in Data Science or other quantitative field is preferred
-
Strong mathematics skills (e.g. statistics, algebra)
-
Certification in Gen/Agentic AI solutions
-
Certification in Platforms – Databricks,AWS is preferred
Experience:
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8+ years of progressive experience in data science and machine learning, with a minimum of 3 years focused on Generative AI and LLM-based systems.
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Demonstrated track record of delivering AI solutions at enterprise scale
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Hands-on experience with full AI/ML lifecycle management: data engineering, feature stores, model training, evaluation, deployment, and monitoring.
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Industry experience especially in Manufacturing Function in a Building Material Industry, Manufacturing, Process or Pharma is preferred.
Required skills:
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Proficiency in Python; strong working knowledge of relevant libraries & frameworks: LangChain, LangGraph, HuggingFace Transformers, PyTorch, scikit-learn, Pandas, and NumPy.
-
Deep experience with LLM APIs (OpenAI, Anthropic, Google, Mistral) and open-source model deployment via Ollama, vLLM, or TGI.
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Solid command of vector databases, semantic search, and knowledge graph technologies for enterprise RAG architectures.
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Proficiency with MLOps tooling: MLflow, Weights & Biases, Kubeflow, or similar; experience with LLMOps tools such as LangSmith.
-
Strong SQL and experience with modern data platforms such as Databricks for AI-ready data preparation.
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Understanding of software engineering best practices: version control (Git), containerization (Docker/Kubernetes), API design (REST/gRPC), and CI/CD pipelines.
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Knowledge of how to benchmark GenAI models beyond simple accuracy (e.g., toxicity, bias, and reasoning depth).
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Exposure to multi-modal AI systems incorporating vision, audio, or structured document understanding (PDFs, tables, charts).
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Good understanding of the GENAI standards (MCP, A2A, A2UI etc.)
Key Responsibility:
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