Software Engineer (ML Performance Optimization)

jobs.frontdoordefense.com - Jobboard; Foster City (CA); On-site; USD 192,000 - 257,000; Full time

Benefits offered by this job

Health insurance

Paid time off

Stock options

Disability insurance

Job summary

Zoox is seeking a Software Engineer specializing in ML Performance Optimization to design and enhance our ML training and inference pipelines for autonomous driving. Located in Foster City, California, this role involves tackling cutting-edge challenges with SOTA accelerators.

You will collaborate across teams, drive performance optimization initiatives, and utilize your experience with frameworks like PyTorch. With a salary range of $192,000 to $257,000, Zoox offers a dynamic environment at the forefront of autonomous technology.

Qualifications

• 4+ years of total experience, including 2+ years of working on large-scale model training or inference platforms.
• Experience with training frameworks leveraging GPUs efficiently for distributed model training.
• Experience using profiling tools to identify model training and serving bottlenecks.

Responsibilities

• Design, implement, and operate performance optimization techniques for ML Training or Inference.
• Collaborate closely with cross-functional teams to align on requirements and architectural decisions.

Skills

Experience with large-scale model training

PyTorch proficiency

GPU-accelerated inference knowledge

Profiling tools experience

Proficient in Python

Proficient in C++

Job description

Software Engineer, ML Performance Optimization

Design and optimize distributed training and inference pipelines for autonomous driving models.

Location: Foster City, California, United States

Compensation: $192,000 - 257,000 USD / year

About The Role

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 robotaxies 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.

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.

Responsibilities

• 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

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 to identify model training and serving bottlenecks.
• Proficient in Python or C++.

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

Zoox is developing the first ground‑up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility‑as‑a‑service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast‑moving and highly execution‑oriented team.

If you need an accommodation to participate in the application or interview process please reach out to [e-mail] or your assigned recruiter.

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.