Develop and maintain ML serving infrastructure, collaborate with teams on architectural decisions, and mentor junior engineers. Role focuses on autonomous driving ML innovations.
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 AI to make autonomous driving as seamless as possible.
The Opportunity
Would you like to enable ML use cases for enabling autonomous driving, scene understanding, and automated mapping at Zoox? This role works across all ML teams within Zoox - Perception, Behavior ML, Simulation, Data Science, Collision Avoidance, as well as with our Advanced Hardware Engineering group specifying our next generation of autonomous hardware. You will significantly push the boundaries of how ML is practiced within Zoox.
We build and operate the base layer of ML tools, deep learning frameworks, inference libraries, and ML infrastructure used by our applied research teams for in- and off-vehicle ML use cases. We coordinate across all of Zoox to make sure that the needs of both the vehicle and ML teams are met. You will play a crucial role in reducing the time it takes from ideation to productionization of cutting-edge AI innovation. 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:
- 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 mentorship
Qualifications
- 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
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.
Follow us on LinkedIn
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.
Zoox Foster City, California, USA Office
4000 E 3rd Ave, Foster City, CA, United States, 94404
Zoox Foster City, California, USA Office
1149 Chess Drive, Foster City, CA, United States, 94404
Zoox Fremont, California, USA Office
47540 Kato Road, Fremont, CA, United States, 94538
Zoox San Francisco, California, USA Office
60 Broadway St, San Francisco, CA, United States, 94111
Similar Jobs
Agency • Gaming • Marketing Tech • Mobile • Analytics
The Data Security Engineer will develop and implement data protection strategies, ensuring compliance with regulations like GDPR and HIPAA while securing sensitive data and collaborating with various teams.
Top Skills:
Analytical ToolsCcpaCismCisspCybersecurityDlp StrategiesGdprHipaaInformation Technology
Big Data • Food • Hardware • Machine Learning • Retail • Automation • Manufacturing
The Senior Scientist I leads ingredient research projects, developing hypotheses and models, conducting experiments, analyzing data, and interacting with technical teams to guide product development in the snack category.
Top Skills:
HaccpStatistical Analysis
Artificial Intelligence • Cloud • Information Technology • Sales • Security • Software • Cybersecurity
The Security Operations Analyst reviews security events, investigates malicious activity, leads incident responses, and documents findings while participating in threat hunting activities.
Top Skills:
LinuxmacOSSecurity Information And Event Management (Siem)SplunkWindows
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
