Software Engineer, ML Performance Optimization

Zoox; Foster City (CA); Hybrid; USD 192,000 - 257,000; Full time

Benefits offered by this job

Health insurance

Paid time off

Zoox Stock Appreciation Rights

Job summary

Zoox is seeking an ML Performance Optimization expert to improve the efficiency of their machine learning models for autonomous driving. This role involves working with cutting-edge technologies and collaborating with diverse teams to push the boundaries of machine learning.

The ideal candidate will have over 4 years of experience, significant knowledge of large-scale model platforms, and proficiency in Python or C++. A competitive salary with comprehensive benefits is offered, including RSUs and a sign-on bonus.

Qualifications

• 4+ years of total experience, including 2+ years in large-scale model training or inference.
• Experience with distributed model training using GPUs.
• Proficiency with GPU-accelerated inference frameworks.

Responsibilities

• Design and implement ML training performance optimization techniques.
• Collaborate with cross-functional teams on model deployment.

Skills

Large-scale model training platforms

GPU efficiency with training frameworks

Profiling tools like NVIDIA Nsight

Proficient in Python or C++

Tools

PyTorch

TensorRT

Job description

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 robotaxes 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 large‑scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible.

The Opportunity

Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting‑edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox – Perception, Prediction, Planner, Simulation, Collision Avoidance – 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, model development, and serving systems that our applied research teams use for in‑ and off‑vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains.

In this role, you will:

• 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.
• 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

Note: You do not have to meet all the requirements below to be considered for this position.

• 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++.

Base Salary Range: $192,000 - $257,000 a year

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign‑on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate’s relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.

Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long‑term care insurance, long‑term and short‑term disability insurance, and life insurance.

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.