Your Responsibilities:
- Explore, clean, and analyse large, complex datasets to uncover patterns, trends, and opportunities that drive actionable insights.
- Develop, train, and validate machine learning, statistical, and predictive models that solve real business problems and deliver measurable impact.
- Design and run experiments (A/B tests, hypothesis tests, simulations) to evaluate ideas, quantify outcomes, and guide decision‑making.
- Collaborate with data engineers, analysts, product managers, and domain experts to translate business requirements into well‑defined modelling tasks.
- Build end‑to‑end ML pipelines—from feature engineering and preprocessing to deployment‑ready model outputs.
Essential skills/knowledge/experience:
- Hands-on experience with GenAI, Gemini or Open source LLMs and develop GenAI applications for Code Translation, Text Extraction, Summarisation and SDLC Optimization etc.
- Hands-on Experience with AI Agents, Chat bots, RAG (Retrieval-Augmented Generation), and vector databases. ( PG vector / croma DB )
- Hands-on Experience with GenAI Performance Evaluation tools like Pegasus, Ragas, DeepEval
- Create Conversational Interface with React JS or other Frontend components, Develop and deploy AI agents using LangGraph and ADK, A2A, MCP
- Strong programming skills in Python (experience with LangChain/LangGraph / LangSmith frameworks) and TypeScript ( preferable )
- Solid understanding of LLMs, prompt engineering, and graph-based workflows.
- Knowledge and implementation of Input and Output guardrails in addressing Hallucination, PII filtering, HAP and Bias etc.
- Implemented security best practices, Experience to address spikes and Denial of wallet attacks, DDoS attack and other Spike arrest strategies
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