Sr. Associate - Machine Learning Engineer

Design, build, and deploy large language model (LLM) and agentic AI systems focusing on reliability, interpretability, safety, and production readiness.

Own evaluation frameworks including automated metrics, testing suites, adversarial testing, and human-in-the-loop evaluations for AI systems.

Implement and operationalize guardrails and MLOps best practices, collaborating with cross-functional partners including compliance and security to ensure auditability and regulatory alignment.

5 to 9 years of applied machine learning or software engineering experience, with at least 2 years on production ML systems.

Bachelor's or Master's degree (B.Tech, M.Tech, MS) in Computer Science or related field.

Strong hands-on experience with large language models: fine-tuning, instruction tuning, retrieval augmentation, embeddings, and agent frameworks.

Proficiency in Python and deep learning frameworks (PyTorch, JAX, TensorFlow); experience deploying cloud services with Kubernetes and model serving technologies.

Experienced in building and operationalizing reliable and safe LLM and agent systems in production environments with strong emphasis on compliance and auditability.

Effective in driving projects end-to-end from prototype to enterprise services in collaboration with product, platform, security, and governance teams.

Familiar with continuous evaluation, adversarial testing, and embedding guardrails to mitigate risks in NLP/LLM systems.