ML Engineer - Data Science

Job Summary

Key Responsibilities
- Design and develop AI Agents and AI Copilots for Statistical Programming, and Biostatistics functions.
- Build intelligent workflows to automate SAS programming, clinical reporting, data validation, and documentation tasks.
- Develop and integrate LLM-based solutions to assist programmers in code generation, review, debugging, and optimization.
- Collaborate with Data Science team and Business Stakeholders to gather requirements.
- Create AI solutions for SDTM, ADaM, TLF generation, clinical study reports, and regulatory submission support.
- Develop Retrieval-Augmented Generation (RAG) systems using clinical and regulatory knowledge repositories.
- Ensure compliance with GxP, FDA, EMA, and data privacy regulations.
- Monitor, evaluate, and improve AI agent performance, accuracy, and reliability.
- Prepare technical documentation, validation plans, and deployment artifacts.

Required Qualifications
- Bachelor's or Master's degree in Statistics, Computer Science,



Data Science, Statistics or a related field.
- 3+ years of experience in AI/ML development, software development, or pharmaceutical analytics.
- Solid programming skills in Python.
- Working knowledge of SAS Programming
- Experience with Large Language Models (LLMs), Generative AI, and AI Agent frameworks.
- Knowledge of prompt engineering, RAG architecture, vector databases, and AI orchestration frameworks.
- Strong analytical and problem-solving skills.

Preferred Qualifications
- Exposure to Biostatistics and Statistical Programming projects.
- Experience with AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar technologies.
- Knowledge of cloud platforms such as AWS, Azure, or GCP.
- Familiarity with MLOps and AI governance practices.

Experience:
- ML Engineering: 3 years (preferred)

Work Location: Remote

📌 Ml Engineer-data Science (India)
🏢 Clinvia
📍 India