Overview
Sr. Principal Machine Learning Engineer (senior individual contributor) to design and deliver production-ready AI/ML systems, including generative AI and agentic AI, for commercial and field engagement use cases.
What you'll do
- Architect and build production-grade machine learning, deep learning, generative AI, and agentic AI systems.
- Lead technical design for RAG, embeddings, semantic search, LLM orchestration, Text2SQL, and recommendation systems.
- Own end-to-end AI/ML lifecycle from problem framing and data prep through monitoring and continuous improvement.
- Design and productionize NLP/LLM capabilities, including evaluation of response quality.
- Implement MLOps/LLMOps practices for CI/CD, monitoring, model registry, experiment tracking, and auditability.
- Apply responsible AI, security-by-design, privacy-by-design, and governance controls across the AI/ML lifecycle.
- Mentor peers and influence engineering practices across teams through reviews, coaching, and standards.
What you'll need
- 6+ years building and deploying production machine learning or AI solutions.
- 3+ years working with generative AI technologies including LLMs, RAG, embeddings, prompt engineering, model evaluation, and agentic workflows.
- Strong proficiency in Python and SQL.
- Hands-on experience fine-tuning deep learning models using PyTorch; TensorFlow experience preferred.
- Experience designing and deploying AI services on AWS, Azure, or GCP.
- Experience implementing MLOps/LLMOps practices including CI/CD, monitoring, observability, experiment tracking, and automated testing.
- Strong software engineering fundamentals including API development, system design, version control, code reviews, and testing.
Details
- Location: India, Bengaluru.
Read the full description and apply on the company’s own careers page.
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