GPU Engineer Houston, TX or San Francisco Bay Area

Bot; Houston, Northern (TX, KY); On-site; USD 120,000 - 180,000; Full time

Job summary

Bot Auto is hiring a GPU Software Engineer to optimize end-to-end GPU performance for real-time autonomous driving workloads. You will work on sensor processing, neural network inference, and GPU-accelerated components in embedded platforms.

Join a cross-functional team of software engineers, AI researchers, and hardware specialists to design onboard GPU architectures for perception, planning, and control modules. Strong CUDA, PyTorch, and C/C++ skills are essential.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or 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.
• Experience deploying or optimizing neural network inference workloads using 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.

Responsibilities

• Optimize end-to-end GPU performance for real-time autonomous driving workloads, including sensor processing and NN inference.
• Develop and optimize parallel computing algorithms and GPU-accelerated components (CUDA).
• Collaborate with cross-functional teams to design and improve onboard GPU software architectures for perception, planning and control modules.
• Profile and analyze bottlenecks across GPU compute, memory access, data movement, synchronization, and CPU–GPU interaction.
• Debug and optimize GPU-based software to improve latency, throughput, and stability on embedded platforms.

Skills

parallel computing

GPU architecture

memory hierarchy

performance optimization

C/C++

Python

neural network inference

real-time embedded systems

sensor data streams

profiling

Education

Bachelor's or Master’s degree in CS/EE or related

Tools

CUDA

Nsight Systems

Nsight Compute

PyTorch

ONNX

TensorRT

NVIDIA Jetson

MPS/MIG

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.

U.S. Standard Demographic Questions

We invite applicants to share their demographic background. If you choose to complete this survey, your responses may be used to identify areas of improvement in our hiring process.

How would you describe your gender identity? Select...

How would you describe your racial/ethnic background? Select...

How would you describe your sexual orientation? Select...

Do you identify as transgender? Select...

Do you have a disability or chronic condition (physical, visual, auditory, cognitive, mental, emotional, or other) that substantially limits one or more of your major life activities, including mobility, communication (seeing, hearing, speaking), and learning? Select...

Are you a veteran or active member of the United States Armed Forces? Select...

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

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.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.

Select...

Voluntary Self-Identification of Disability

Form CC-305 Page 1 of 1 OMB Control Number 1250-0005 Expires 04/30/2026
Why are you being asked to complete this form?

We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. We have a goal of having at least 7% of our workers as people with disabilities. The law says we must measure our progress