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.
Top Skills
What We Do
Zoox is an autonomous mobility company that was founded to provide a safer, cleaner, and more enjoyable future on the road. To achieve that goal, the company has spent the past 10 years creating a purpose-built robotaxi that gives the world a better way to ride.
Why Work With Us
At Zoox, we are working to solve one of the greatest technological challenges of our generation.
From the beginning, we have been focused on our goal of reimagining transportation from the ground up. We are a mission-driven community of innovators working together to create a safer, cleaner, and more enjoyable future on the road.
Gallery
