Key Responsibilities:

• Lead the design, development, and deployment of advanced machine learning models and algorithms for various applications.
• Build and optimize chatbots and autonomous agents using LLM endpoints and frameworks like LangChain, Semantic Kernel, or similar.
• Implement vector search using technologies such as FAISS, Weaviate, Pinecone, or Milvus for semantic retrieval and RAG (Retrieval-Augmented Generation).
• Collaborate with data engineers and product teams to integrate ML models into production systems.
• Monitor and maintain deployed models, ensuring performance, scalability, and reliability.
• Conduct experiments, A/B testing, and model evaluations to improve system accuracy and efficiency.
• Stay updated with the latest advancements in AI/ML, especially in agentic systems and generative AI.

Required Skills & Qualifications

• 5+ years of experience in Machine Learning, Deep Learning, and AI system design.
• Strong hands-on experience with Agentic AI frameworks and LLM APIs (e.g., OpenAI).
• Proficiency in Python and ML libraries like scikit-learn, XGBoost, etc.
• Experience with AWS services such as SageMaker, Lambda, S3, EC2, and IAM.
• Expertise in Databricks for collaborative data science and ML workflows.
• Solid understanding of vector databases and semantic search.
• Hands-on experience with MLOps including containerization (Docker, Kubernetes), CI/CD, and model monitoring along with tools like MLflow,

• Experience with RAG pipelines & LangChain.
• LLM orchestration, or agentic frameworks.
• Knowledge of data privacy
• Exposure to real-time inference systems and streaming data.
• Experience in regulated industries such as healthcare, biopharma
• Proven ability to scale AI teams and lead complex AI projects in high-growth environments