Software Engineer - Planner GPU Compute

zoox

4100

Boston, MA

Posted on: 2026-09-27

Category: emobility

Ready to make this your next chapter?

Let zoox know you found them on WorkInGreen. It helps more companies post climate jobs here.

Apply to job

Employment type:

Full time

Experience required:

Intermediate

Salary

$209,000.00 - $263,000.00

About the company:

Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.

Zoox made the world’s first purpose-built commercial robotaxi, combining advanced self-driving hardware and software. In order to ensure safe operation, low latency and consistent resource utilization are critical. The Planner Compute team is responsible for the performance of the largest single software component within the autonomy stack, the motion planner.

The Planner Compute team is looking for an expert in GPU performance. You will instrument, monitor, analyze and optimize GPU-based algorithms that are performance-critical for our solution. The scope for GPU usage ranges from machine learning inference to custom CUDA kernels written specifically for the motion planner.

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.

In this role, you will:

Analyze performance metrics to identify GPU hotspots and optimizations

Contribute to the adaptation of our current planner to multiple GPU architectures with different resources

Optimize ML models for latency and GPU memory usage

Support engineers within Planner as a subject matter expert on CUDA & GPU performance

Qualifications

BS in computer science or related field and 6+ years of experience.

Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and experience debugging/optimizing GPU kernels using tools like Nsight.

Strong knowledge of C++ and experience in large code bases, comfortable in Linux development environments.

Experience in development, debugging, and profiling of complex multiprocess systems (e.g., robotic systems, game engines).