Senior ML Infrastructure Engineer - Embodied AI Scaling Foundations
Core
Build critical infrastructure to accelerate machine learning model training and evaluation workflows for autonomous driving models.
Role type
Senior ML Infrastructure Engineer
Builds
Scalable platforms and tools for ML training/evaluation pipelines
Domain
Autonomous driving / Machine Learning Infrastructure
Deliverable
production ML models
Required skills
Distributed systems design, MLOps practices, Cloud infrastructure, Containerization (Docker, Kubernetes), Python or C++ coding, System architecture, Technical leadership
Preferred skills
Distributed training methodologies, GPU/CPU cluster scaling, Deep learning frameworks (PyTorch, TensorFlow), Performance profiling, Advanced build systems (Bazel, Buck, Cmake)
Technologies
Docker, Kubernetes, Python, C++, PyTorch, TensorFlow, Bazel, Buck, Blaze, Cmake
Responsibilities
Design and deploy scalable ML training/evaluation platforms, Own end-to-end technical projects and architectural decisions, Mentor and onboard junior engineers, Collaborate with partner teams on system integration
Seniority
Senior, hands-on IC with mentorship
