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Salary
$209k – $263k per year
Location
Hybrid (Boston, Foster City, United States)
Seniority
Senior · 6+ years exp
Visa
H-1B filings in 12 months: 373 · for this role: 169 · green card filings: 120
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 11, 2026. First seen by Alion on Sep 27, 2026. Zoox scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Zoox is an American autonomous vehicle company founded in 2014 that designs a purpose-built robotaxi rather than retrofitting an existing car. Its vehicle has no steering wheel or driver position, seats four passengers facing each other, drives equally well in either direction and was developed alongside the sensors, compute and software that operate it, which required the company to certify the design under its own self-certification of federal motor vehicle safety standards. Amazon acquired the company in 2020 and it has since begun public robotaxi service in Las Vegas and San Francisco while testing in several other American cities.

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.

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).

Bonus Qualifications

    GPU kernel development experience

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