Engineering Manager, ML Platform (Training) - Zoox

Job Title: Engineering Manager, ML Platform (Training)
Job Location: Foster City, CA
Job Listing URL: https://jobs.lever.co/zoox/b2f3d1ea-82ac-414b-b082-e7c155790bed
Job Description: Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in ML and CV to make autonomous driving as seamless as possible.

The Opportunity
Are you excited to manage our ML Training Infrastructure that enables autonomous driving? You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, etc. and our Advanced Hardware Engineering group and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.

This team builds and operates the base layer of ML tools, deep learning frameworks, model repository and model lifecycle management tools used by our applied research teams for in- and off-vehicle ML use cases. You will lead a team of strong software engineers and act as a force multiplier for our internal customers. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here.
In this role, you will
Vision: Develop and execute a strategic vision for our ML training platform ensuring scalability, reliability, and performance to support our autonomous vehicle operations.
Technical acumen: Lead the design, implementation, and operation of a robust and efficient ML training platform to enable the training, experimentation, validation, and monitoring of ML models.
Hiring: Attract, hire, and inspire a diverse world-class engineering team, fostering a culture of innovation, collaboration, and excellence.
Partnership: Collaborate closely with x-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers to define requirements and align on architectural decisions.
Mentorship: Enable the engineers in the team to grow their careers by providing the right opportunities along with clear and timely feedback.
Qualifications
8+ years of total experience, including 3+ years of engineering management experience.
Excellent leadership skills with a demonstrated ability to build and manage high-performing engineering teams.
Experience enabling large-scale, high throughput and distributed model training infrastructure.
Experience with training frameworks like PyTorch, Hugging Face, Ray, JAX, etc., leveraging GPUs, TPUs, or Trainium.
Experience building model lifecycle management tools and managing AWS costs for our ML needs.