10+ Years | Classical ML + GenAI+ ML-Ops
Overview
An accomplished Principal / Expert Data Scientist with 10+ Year of experience and having deep expertise & hands-on in classical machine learning, GenAI Applications & ML lifecycle,
Key Responsibilities
1. Machine Learning & Statistical Modelling
- Build and optimize complex ML models: regression, classification, clustering, sequence models, time series forecasting.
- Lead sophisticated feature engineering and data quality analysis.
- Apply statistical modelling techniques, experimental design, and Performance evaluation.
- Develop scalable and maintainable ML pipelines for structured and unstructured data.
2. GenAI & LLM Systems
- Architect and develop LLM-based applications using SOTA LLM's.
- Build RAG pipelines using vector databases (faiss, aisearch, opensearch, PG vector etc).
- Integrate GenAI systems with enterprise apps, APIs, and data sources.
- Model Context Protocol (MCP) & Tooling
- Exposure of Agentic systems and multi-agent workflows
3. Agentic Systems & Model Context Protocol (MCP)
- Exposure to agentic system design, including tool‑calling workflows, planner–executor patterns, and multi‑agent coordination.
- Integrate memory architectures such as episodic, semantic, and vector‑based long‑term memory within agent workflows.
- Implement and manage Model Context Protocol (MCP) servers to enable seamless connectivity between LLMs, tools, APIs, and enterprise applications.
- Collaborate with engineering teams to build reliable, extensible agent tooling and ensure smooth integration into production environments.
4. Cloud ML-Ops & Quality
- ML Modelling, data drift, concept drift, model quality monitoring.
- Hands‑on experience across AWS/ Azure/ Databricks, with flexibility to work on any cloud platform.
· Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub, Markdown)
5. Leadership & Collaboration
- Lead technical direction for AI solutions.
- Work with product teams to define AI features.
