Senior Staff Machine Learning Engineer

Lead the architecture and development of large-scale cloud ML systems end to end, including data pipelines, training infrastructure, model serving, monitoring, and retraining.

Design and deploy scalable production cloud solutions utilizing Gen-AI, agentic AI, DNN, traditional ML models, and ETL pipelines with emphasis on distributed, fault-tolerant services under SLAs.

Set engineering standards and mentor senior engineers while collaborating cross-functionally to implement data-driven business solutions and maintain ROI models for data science initiatives.

B.Tech, M.Tech, or PhD in Data Science, Computer Science, Electrical Engineering, Statistics, Mathematics or related.

Minimum 8 years in machine learning or related domain with at least 5 years building and deploying production ML systems at scale.

Strong distributed systems and software engineering skills including cloud experience (AWS preferred) and programming in Python (required).

Proven expertise with ML fundamentals, statistics, large-scale software engineering, and production ML pipeline operations.

Senior-level individual contributor with demonstrated ability to influence technical decisions across teams.

Experienced in both data engineering (ETL pipelines) and ML model lifecycle including training, tuning, deployment, and monitoring at scale.

Strong background in Gen-AI technologies, distributed cloud architectures, and modern ML ops practices including CI/CD, observability, and cost/reliability trade-offs on public cloud.