Senior Software Engineer, ML Platform

• Build the Zoox Training framework leveraged by all ML teams within Zoox. This framework needs to be highly scalable, reliable, and efficient.
• Build the Off-vehicle inference service powering our Foundational models and the models that improve our rider experiences.
• Lead the design, implementation, and operation of 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.
• Enable the junior engineers in the team to grow their careers by providing technical guidance and mentorship.

This role enables innovations in ML and CV to make autonomous driving as seamless as possible, contributing to Zoox's mission to reimagine transportation with safe, reliable, clean, and enjoyable autonomous robotaxis for everyone.

• 4+ years of ML infrastructure experience.
• Experience building large-scale distributed multi-node GPU model training and/or high throughput, low latency serving use cases.
• Experience with training frameworks like PyTorch and OSS frameworks like Ray.
• Experience with GPU-accelerated inference using TensorRT, Ray Serve, or a similar framework.
• Experience working with cloud providers like AWS.

No specific benefits, compensation, or perks mentioned in the job description.

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market, aiming to provide the next generation of mobility-as-a-service in urban environments.