Senior / Staff / Principal ML Systems Engineer
Core
Building and optimizing large-scale infrastructure for machine learning, including data platforms, training systems, and production inference for multimodal datasets.
Role type
Senior/Staff/Principal ML Systems Engineer
Builds
Data platforms, ML training infrastructure, evaluation systems, model lifecycle management tools, and production inference systems for video and multimodal data.
Domain
Entertainment / AI Infrastructure / High-Performance Computing
Deliverable
infrastructure
Required skills
Python engineering, distributed systems design, large-scale data pipeline optimization, PyTorch, systems design, debugging, performance trade-off analysis
Preferred skills
Video/multimodal ML pipelines, embeddings/vector search, production inference operations, React for internal tools
Technologies
PyTorch, distributed training frameworks, columnar data formats, data lake architectures
Responsibilities
Build and evolve data platforms for curating large-scale multimodal datasets; Design systems to index and process thousands of videos via ML pipelines; Build and optimize infrastructure for large-scale model training; Develop tooling for experiment tracking and model comparison; Design infrastructure for model versioning and deployment; Build and optimize production inference systems.
Seniority
Senior to Principal, hands-on IC with increasing architectural leadership and mentorship scope
