Software Engineer, ML Performance Optimization
Zoox
Apply to this jobIn this role, you will:
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Design, implement, and operate cutting-edge ML Training OR Inference performance optimization techniques to scale our VLM, VLA, and Foundational models and deploy them efficiently in our robotaxi.
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Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.
Qualifications
- 4+ years of total experience, including 2+ years of working on large-scale model training or inference platforms.
- Experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training.
- Experience with GPU-accelerated inference using TensorRT 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 or C++.
Compensation (from employer):
192000–257000 USD per year
Summary
Optimize ML models for autonomous driving; collaborate across teams on scalable ML solutions
Job title
Software Engineer, ML Performance Optimization
Experience level
4+ years
Minimum experience
4+ years exp
Industry
software
Location requirements
Foster City, CA; remote work not specified
Salary
$192k–$257k
Visa sponsorship
H-1B sponsor history
Management role
No
Required skills
Preferred skills
Specializations
Structured locations inferred from the posting.
Foster City, CA, USA