Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to
[email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
In this role, you will:
Build the off-vehicle inference service powering our Foundational models (LLMs & VLMs) and the models that improve our rider experiences.Lead the design, implementation, and operation of a robust and efficient ML serving infrastructure to enable the 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 mentorshipQualifications
4+ years of ML model serving infrastructure experience Experience building large-scale model serving using GPU and/or high QPS, low latency serving use cases.Experience with GPU-accelerated inference using RayServe, vLLM, TensorRT, Nvidia Triton, or PyTorch.Experience working with cloud providers like AWS and working with K8s