Machine Learning Engineer

Build and evolve the offline ML infrastructure that powers training data generation, ML workflows, and distributed model training at scale. You’ll construct reliable data pipelines for datasets and experimentation, implement dataset validation/monitoring/testing for reproducibility, and collaborate with ML engineers to support iteration. The role bridges research and production by translating advanced ML ideas into scalable systems using tools like PyTorch, Ray, Airflow, and Flyte.