GPU Engineer

Bot-Auto; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Bot Auto is hiring an experienced GPU-focused engineer to advance autonomous driving workloads. You will optimize end-to-end GPU performance, including sensor processing (camera, LiDAR) and neural network inference, and collaborate with software and hardware teams to optimize onboard GPU software for perception, planning, and control subsystems.

The role emphasizes CUDA-based development, profiling, and deployment on embedded platforms, with opportunities to work across SF Bay Area or relocation

Qualifications

• Bachelor's or Master's degree in CS/EE or related field.
• Strong knowledge of parallel computing, GPU architecture and memory hierarchy.
• Experience profiling GPU apps with Nsight or similar tools.
• Experience deploying/optimizing neural network inference (PyTorch/ONNX/TensorRT).
• Experience with real-time embedded systems and sensor data streams.

Responsibilities

• Optimize end-to-end GPU performance for real-time autonomous driving workloads.
• Develop and optimize CUDA-based parallel computing algorithms.
• Design and improve onboard GPU software architectures for perception, planning, and control modules.
• Profile and analyze bottlenecks across GPU compute, memory, and CPU-GPU interaction.
• Debug and optimize GPU-based software to reduce latency and improve throughput on embedded platforms.

Skills

Parallel computing

GPU programming

C/C++

Python

Profiling GPU

Education

Bachelor's or Master's degree

Tools

CUDA

NVIDIA Nsight

TensorRT

PyTorch

ONNX

Job description

At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.

You would collaborate with software engineers, AI researchers, and hardware specialists to develop high-performance solutions that meet the stringent requirements of autonomous driving applications. This is an exciting opportunity to work on next-generation transportation technology and make a meaningful impact on the future of mobility.

Key Responsibilities

• Optimize end-to-end GPU performance for real-time autonomous driving workloads, including sensor processing (e.g., camera, LiDAR) and neural network inference.
• Develop and optimize parallel computing algorithms and GPU-accelerated components using technologies such as CUDA.
• Collaborate with cross-functional teams to design and improve onboard GPU software architectures that meet the computational requirements of perception, planning, and control modules.
• Profile and analyze bottlenecks across GPU computation, memory access, data movement, synchronization, and CPU-GPU interaction.
• Debug and optimize GPU-based software to improve latency, throughput, resource utilization, and runtime stability on embedded platforms.

Qualifications

Required:

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• Strong knowledge of parallel computing principles, GPU architecture, memory hierarchy, and performance optimization techniques.
• Experience profiling GPU applications using tools such as NVIDIA Nsight Systems, Nsight Compute, or equivalent tools.
• Experience deploying or optimizing neural network inference workloads using technologies such as PyTorch, ONNX, and TensorRT.
• Experience with real-time embedded systems and handling large data streams from sensors (camera, LiDAR, radar).
• Strong proficiency in C/C++ and Python.

Preferred:

• 3+ years of experience in GPU programming and optimization (e.g., CUDA, OpenCL, Vulkan).
• Experience with NVIDIA Jetson Thor, NVIDIA DRIVE Thor, or similar embedded GPU platforms.
• Experience with model quantization, including FP8 and NVFP4.
• Experience managing concurrent GPU workloads and resource isolation using technologies such as NVIDIA Multi-Process Service (MPS), Multi-Instance GPU (MIG), or other related technologies.
• Experience with GPU-accelerated sensor data compression, including camera, LiDAR, or other onboard sensor data.

Our primary office location for this role is Houston, TX. Would you be open to relocating to Houston? If Houston is not an option, would you be open to working at our San Francisco Bay Area location instead? Please specify below:

Are you legally authorized to work in the US? * Select...

Do you now, or will you in the future, require immigration sponsorship for work authorization (for example, H-1B status)? * Select...

If Yes: - What type of visa sponsorship will you require? - Do you currently hold a valid U.S. visa?

As set forth in Bot Auto's Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.