Project Lead

Job Summary: -

AI/ML Engineer with good hands-on experience of 3+ years in developing state of the art and scalable Machine Learning models and their operationalization, as well as designing and deploying AI Agent workflows and pipelines, leveraging off-the-shelf workbench production.

Job Responsibilities: -

• Hands on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib
• Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.)
• Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence
• Good understanding of any of the cloud platform – AWS, Azure or GCP
• Understanding of Commercial Pharma landscape and Patient Data / Analytics would be a huge plus
• Should have an attitude of willingness to learn, accepting the challenging environment and confidence in delivering the results within timelines. Should be inclined towards self motivation and self-driven to find solutions for problems.
• Agent Ops: Hands-on experience in designing, deploying, and monitoring AI agent workflows using any frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or equivalent agentic orchestration tools
• Experience with prompt engineering, tool/function calling, RAG (Retrieval-Augmented Generation) pipelines, and memory/context management for multi-step agentic systems
• Familiarity with LLM lifecycle management including fine-tuning, evaluation, guardrails, and deployment of foundation models via APIs (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or equivalent)
  
  

Experience operationalizing agent-based systems including observability, tracing, latency optimization, cost monitoring, and failure handling for production-grade deployments