Lead ML Performance Optimization for autonomous driving, collaborating across teams, implementing optimization techniques, and mentoring engineers for career growth.
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 lead our ML Performance Optimization initiatives and make our Training and Inference platform that enables autonomous driving as fast and efficient as possible? You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and Advanced Hardware Engineering group and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.
We build and operate the base layer of ML tools, deep learning frameworks, and inference systems 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:
- Develop and execute a strategic vision for the ML Performance Optimization team to unlock ML innovation in autonomous driving and rider experience.
- Lead the design, implementation, and operation of cutting-edge ML Training and inference performance optimization techniques.
- Collaborate closely with x-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.
- Enable the engineers in the team to grow their careers by providing technical guidance and mentorship.
Qualifications
- Strong experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training.
- Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks.
- Experience using profiling tools like NVIDIA's Nsight or PyTorch's Profiler for identifying model training and serving bottlenecks.
- Proficient in Python and C++
- Experience with model compression techniques to reduce model size and improve performance.
Bonus Qualifications
- 10+ years of total experience, including 4+ years of working on large-scale model training or inference platforms.
- Excellent leadership skills with a demonstrated ability to lead high-performing engineering teams.
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.
Top Skills
C++
Python
PyTorch
Ray Serve
Tensorrt
Similar Jobs
Marketing Tech • Social Media • Software • Analytics • Business Intelligence
The Adoption Consultant drives customer satisfaction and retention, ensuring effective platform adoption through training and proactive health monitoring, while collaborating with internal teams.
Top Skills:
Customer Success SoftwareGainsight
.png)
5 Minutes Ago
Digital Media • eCommerce • Information Technology • Marketing Tech • Retail • Social Media • Analytics
The intern will analyze customer feedback, improve product education, enhance customer experience on Amazon, and collaborate across teams to optimize listings and resolve issues.
Top Skills:
Ai-Driven Discovery ToolsAmazon
eCommerce • Fintech • Food • Mobile • Social Impact
Design and build scalable distributed systems for financial transactions, leveraging AI tools to improve engineering workflows, while collaborating with cross-functional teams.
Top Skills:
DjangoExpressFastifyRuby on Rails
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
