Software Engineer, ML Platform
Build and operate scalable ML training frameworks, distributed infrastructure, and model lifecycle tools to power foundational models, reinforcement learning, and other ML use cases across Zoox's autonomous driving teams. Requires 2+ years ML infrastructure experience with PyTorch, DeepSpeed, JAX, Ray and AWS.
About the job
Responsibilities
- Build the Zoox Training framework leveraged by all ML teams within Zoox. This framework needs to be highly scalable, reliable, and efficient.
- Design, implement, and operate a robust and efficient ML platform to enable the training, validation, serving, and monitoring of ML models.
- Collaborate closely with cross-functional teams, including ML researchers, software engineers, and data engineers, to define requirements and align on architectural decisions.
Requirements
- 2+ years of ML infrastructure experience.
- Experience with training frameworks like PyTorch, DeepSpeed, JAX, Ray, etc.
- Experience working with cloud providers like AWS.
Nice-to-Haves
- Experience with building large-scale, cost-efficient distributed model training and ML compute infrastructure.
- Experience with building model lifecycle management tools and experimentation.
Skills
PyTorch, Deepspeed, JAX, Ray, AWS, ML Infrastructure, Distributed Training, Model Lifecycle Management
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