Data Science + AI Engineer7 (Chennai)

Description Must have skills Python, ML, SQL, Vector, LLM, Git, CI/CD, docker GCP is good to have Requirements Experience: 5+ years of professional experience in Data Science, Machine Learning, or AI Development. Programming Languages: Exceptional proficiency in Python and solid SQL skills. Google Cloud Platform (GCP): Hands-on experience with GCP infrastructure, specifically Vertex AI, BigQuery, and deployment services (Cloud Run/GKE). Generative AI & LLMs: Proven experience working with Large Language Models, with a strong mandatory focus on the Google Gemini API (Pro, Flash, etc.) and Vertex AI Studio. AI Frameworks: Familiarity with orchestration frameworks like LangChain or LlamaIndex for building complex LLM applications. Vector Databases: Experience working with vector search solutions (e.g., Vertex AI Vector Search, Pinecone, or pgvector). Data Science Toolkit: Proficiency with standard Python libraries (Pandas, NumPy, Scikit-Learn, TensorFlow/PyTorch). Software Engineering Best Practices: Experience with Git, CI/CD pipelines, and containerization (Docker). Preferred Qualifications Experience fine-tuning foundational models on custom datasets. Familiarity with data governance, AI security, and responsible AI practices within an enterprise environment. Job responsibilities GenAI Application Development: Design, build, and deploy Generative AI applications using Googles latest Gemini models via Vertex AI. RAG Architecture Implementation: Develop robust Retrieval-Augmented Generation (RAG) pipelines, integrating proprietary enterprise data with Gemini to ground model responses and reduce hallucinations. GCP Ecosystem Integration: Utilize GCP services effectively, including Vertex AI, BigQuery, Cloud Storage, Cloud Functions, and Cloud Run, to build secure and scalable AI pipelines. Model Deployment & MLOps: Containerize applications and deploy models into production environments, ensuring proper monitoring, logging, and performance tracki .