On-site opportunity at
ZooxSoftware Engineer, ML Performance Optimization
Zoox is designing and building purpose-built autonomous robotaxis from the ground up to transform urban mobility and transportation. The ML Platform team at Zoox operates the…
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About This Role
Zoox is designing and building purpose-built autonomous robotaxis from the ground up to transform urban mobility and transportation. The ML Platform team at Zoox operates the fundamental infrastructure, development tools, and serving systems that power machine learning applications both on and off the vehicle. This position suits an engineer interested in advancing machine learning capabilities for autonomous driving systems. In this role, the software engineer will drive performance optimization initiatives…
Job Description
Zoox is designing and building purpose-built autonomous robotaxis from the ground up to transform urban mobility and transportation. The ML Platform team at Zoox operates the fundamental infrastructure, development tools, and serving systems that power machine learning applications both on and off the vehicle. This position suits an engineer interested in advancing machine learning capabilities for autonomous driving systems.
In this role, the software engineer will drive performance optimization initiatives for machine learning models, working with state-of-the-art accelerators and modern distributed training methodologies. The engineer will collaborate across multiple autonomy departments, including perception, prediction, planning, simulation, and collision avoidance. Responsibilities include building systems that scale foundational models, Vision-Language Models, and Vision-Language-Action models for efficient robotaxi deployment.
Candidates will join a technical environment focused on execution, working alongside applied research teams and fellow software engineers. The role involves designing and operating optimization strategies such as quantization, pruning, and distillation. Qualified professionals with a background in machine learning platforms or model optimization will find growth opportunities as the organization scales its robotaxi fleet and explores new machine learning domains.
Responsibilities
- Design, implement, and operate machine learning training or inference performance optimization techniques
- Scale foundational models, VLMs, and VLAs for efficient deployment in robotaxis
- Collaborate with ML researchers, software engineers, data engineers, and hardware engineers to establish requirements and architectural decisions
Requirements
- 4+ years of total professional experience
- 2+ years of experience working on large-scale model training or inference platforms
- Experience with training frameworks like PyTorch and utilizing GPUs for distributed model training
- Experience with GPU-accelerated inference using frameworks such as TensorRT
- Experience using profiling tools like PyTorch's Profiler or NVIDIA's Nsight to identify bottlenecks
- Proficiency in Python or C++
Core Skills
Frequently Asked Questions
What is the location and remote status for this role?
The job posting does not specify a location, but it lists the remote status as on-site.
What is the employment type?
The position is a full-time role.
What are the primary technical requirements for applying?
Applicants must have at least four years of total experience, with a minimum of two years focused on large-scale model training or inference platforms. Candidates also need proficiency in Python or C++, experience with GPU training frameworks like PyTorch and inference tools like TensorRT, and familiarity with profiling tools such as NVIDIA's Nsight.
Does the job posting state a salary?
No, the salary is not specified in the posting.
How can applicants request interview accommodations?
Candidates needing an accommodation can reach out by email to accommodations@zoox.com or contact their assigned recruiter.
Sample Interview Questions
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