Senior Machine Learning Engineer

Responsibilities

• Design, implement, and optimize agentic AI components, including context engineering, memory management, and prompts. - Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights. - Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes. - Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement. - Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience. Required Qualifications

• B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field. - 4-6 years of hands-on industry experience with demonstrable ownership and delivery. - Strong understanding of machine learning fundamentals, data pipelines, and model evaluation. - Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus. - Working knowledge of LLM core concepts, prompt design, and agentic design patterns. - Strong communication skills and a passion for shaping emerging AI paradigms. Desired Qualifications

• Prior experience building and deploying AI agents or LLM applications in production. - Familiarity with modern agentic AI frameworks (e.g., LangGraph, LangChain, CrewAI). - Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS). - Exposure to LLM Ops - infrastructure optimization, observability, latency, and cost monitoring.