Senior ML Infrastructure Engineer - Embodied AI
Core
Design, implement, and deploy scalable platforms and tools supporting machine learning training and evaluation workflows for autonomous driving models.
Role type
Senior ML Infrastructure Engineer
Builds
Scalable, high-performance training platforms and MLOps pipelines for autonomous vehicle models
Domain
Autonomous driving / Machine Learning Infrastructure
Deliverable
production ML models
Required skills
Distributed systems design, ML workflows in production, Cloud infrastructure, MLOps practices, Python, C++, API design, System reliability
Preferred skills
Distributed training methodologies, GPU/CPU cluster scaling, Deep learning frameworks (PyTorch, TensorFlow), Performance profiling, Build systems (Bazel, Buck, CMake), Containerization (Docker, Kubernetes)
Technologies
Python, C++, PyTorch, TensorFlow, Docker, Kubernetes, Bazel, Buck, Blaze, CMake
Responsibilities
Design and deploy scalable ML training and evaluation platforms; Drive complex technical projects with ownership of implementation and code quality; Collaborate on architectural decisions; Partner with teams to maximize platform adoption; Identify technical improvements for performance and reliability; Mentor junior engineers
Seniority
Senior, hands-on IC
