Senior GPU Compute Engineer – Planner (Hybrid)

Engg; Boston (MA); Hybrid; USD 237,000 - 298,000; Full time

Benefits offered by this job

Zoox RSUs

Zoox Stock Appreciation Rights

Health insurance

Paid time off

Sign-on bonus

Job summary

Zoox in Boston, MA / Foster City, CA seeks a Senior Software Engineer for Planner GPU Compute to optimize GPU-based motion planning components. You will analyze GPU performance, profile with Nsight, and adapt the planner across architectures to reduce latency and memory usage.

The role blends ML inference and CUDA kernel work, with collaboration across the Autonomy Software group. Qualifications include a BS in CS with 3+ years, strong CUDA/C++, Linux experience, and hands-on GPU kernel

Qualifications

• BS in computer science or related field and 3+ years of experience.
• Strong knowledge of CUDA as applied to recent GPU microarchitectures (e.g., Ampere, Blackwell) and 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).

Responsibilities

• 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

Skills

CUDA expertise

C++

Linux development

Nsight profiling

GPU performance optimization

Machine learning inference

Education

BS in Computer Science

Tools

Nsight

CUDA Toolkit

GDB

Job description

Zoox in Boston, MA / Foster City, CA seeks a Senior Software Engineer for Planner GPU Compute to optimize GPU-based motion planning components. You will analyze GPU performance, profile with Nsight, and adapt the planner across architectures to reduce latency and memory usage.

The role blends ML inference and CUDA kernel work, with collaboration across the Autonomy Software group. Qualifications include a BS in CS with 3+ years, strong CUDA/C++, Linux experience, and hands-on GPU kernel