On-site opportunity at
ZooxSenior/Staff Software Engineer, ML Performance Optimization
Zoox is designing purpose-built, fully autonomous robotaxis and creating an ecosystem to deliver mobility services in urban areas. The organization is actively deploying these self-driving vehicles…
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AI Summary
This role involves leading machine learning performance and efficiency initiatives across both on-vehicle and off-vehicle autonomous driving systems. You will apply optimization techniques such as quantization, pruning, and distributed training in Python and C++ to speed up inference and model training. Additionally, you will partner directly with domain teams like Perception and Planning to shape ML efficiency roadmaps and mentor engineering staff.
About This Role
Zoox is designing purpose-built, fully autonomous robotaxis and creating an ecosystem to deliver mobility services in urban areas. The organization is actively deploying these self-driving vehicles on public roads and expanding its technological capabilities. The ML Platform group at Zoox constructs the foundational layer of machine learning tools, serving systems, and model development infrastructure utilized across applied research teams for both on-vehicle and off-vehicle applications. This position focuses on leading…
Job Description
Zoox is designing purpose-built, fully autonomous robotaxis and creating an ecosystem to deliver mobility services in urban areas. The organization is actively deploying these self-driving vehicles on public roads and expanding its technological capabilities. The ML Platform group at Zoox constructs the foundational layer of machine learning tools, serving systems, and model development infrastructure utilized across applied research teams for both on-vehicle and off-vehicle applications.
This position focuses on leading ML Performance Optimization initiatives to ensure models powering autonomous driving operate swiftly and efficiently. Professionals in this capacity utilize state-of-the-art accelerators alongside modern methodologies in distributed training, quantization, distillation, and pruning. The selected individual will coordinate directly with cross-functional groups such as Perception, Prediction, Planner, Simulation, and Collision Avoidance, serving as a technical multiplier for internal engineering teams.
Suitable candidates possess strong programming capabilities in Python and C++, extensive backgrounds with distributed training frameworks like PyTorch, and hands-on familiarity with GPU-accelerated inference tools. This opportunity welcomes engineers interested in shaping the roadmap for robotaxi machine learning efficiency and mentoring team members.
Responsibilities
- Formulate and execute a strategic roadmap for the ML Performance Optimization team to advance autonomous driving capabilities
- Design, implement, and manage advanced machine learning training and inference performance optimization techniques
- Scale foundational models, Vision-Language Models, and Vision-Language-Action models for efficient deployment in robotaxis
- Partner cross-functionally with machine learning researchers, software engineers, data engineers, and hardware specialists to establish requirements and architectural choices
- Provide technical mentorship and guidance to foster the career growth of engineers on the team
Requirements
- Extensive background using training frameworks such as PyTorch for distributed model training with GPUs
- Familiarity with GPU-accelerated inference utilizing TensorRT or comparable frameworks
- Practical use of profiling utilities like PyTorch's Profiler or NVIDIA's Nsight to locate model training and serving bottlenecks
- Proficiency in C++ and Python programming languages
- Familiarity with model compression methods aimed at reducing footprint and boosting speed
Qualifications
- Ten or more years of total professional experience
- Four or more years focused on large-scale model training or inference platforms
- Demonstrated leadership abilities in guiding high-performing engineering teams
Core Skills
Frequently Asked Questions
What is the employment type for this position?
The role is a full-time position.
What is the remote work policy?
The job posting indicates that the position is on-site.
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Role DNA
This staff-level role demands deep technical mastery in GPU hardware and ML optimization alongside strong cross-team leadership skills to navigate high-stakes autonomous vehicle engineering.
Salary Analysis
While salary was not disclosed in the posting, market rates for Senior/Staff ML Performance Engineers in the San Francisco Bay Area typically range from $210,000 to $310,000 in base salary, excluding equity and bonus targets.
Employer-Listed Salary
Not disclosed
As stated in this job posting.
Jobsiz Platform Estimate
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