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Gpu Engineer Jobs (NOW HIRING)

Bot Auto

GPU Engineer

Houston, TX · On-site

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 ...

Bot Auto

GPU Engineer

Houston, TX · On-site

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 ...

Qualcomm

GPU Engineer

Santa Clara, CA · On-site

$155K - $200K/yr

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: This individual possesses the solid engineering fundamentals and understanding with some supervision in the architecting ...

Fuse Energy

Founding GPU Engineer

We're looking for a Founding GPU Engineer to develop and optimise GPU-accelerated software for data centre systems: low-level performance engineering for large-scale compute clusters, tying GPU ...

Qualcomm

Senior GPU Engineer

San Diego, CA · On-site

$133.60 - $200.40/hr

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: This individual independently plans, performs the moderately‑defined responsibility for architecting, designing ...

Qualcomm

Senior GPU Engineer

San Diego, CA · On-site

$137K - $200K/yr

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: This individual independently plans, performs the moderately-defined responsibility for the architecting, designing ...

Nutanix

Staff GPU Engineer

San Diego, CA · On-site

$162 - $243/hr

Job Area:Engineering Group, Engineering Group > GPU ASICS EngineeringGeneral Summary:This individual leads, plans, synthesizes ambiguous or conflicting requirements and performs the complex ...

New

Qualcomm

Staff GPU Engineer

San Diego, CA · On-site

$161K - $242K/yr

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: This individual leads, plans, synthesizes ambiguous or conflicting requirements and performs the complex responsibility ...

Qualcomm

Staff GPU Engineer

San Diego, CA · On-site

$162 - $243/hr

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: This individual leads, plans, synthesizes ambiguous or conflicting requirements and performs the complex responsibility ...

Qualcomm

GPU DV Engineer

Santa Clara, CA · On-site

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation ...

Qualcomm

GPU HLM Engineer

San Diego, CA · On-site

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation ...

YO AI Labs

GPU Programmer - Remote

Chicago, IL · Remote

$60 - $85/hr

GPU Programmer - Remote Job Type: Contractor Location: Remote Job Overview We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and LLM ...

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How much do gpu engineer jobs pay per year?

As of Aug 28, 2026, the average yearly pay for gpu engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What does a GPU engineer do?

A GPU Engineer designs, develops, and optimizes graphics processing units (GPUs) for applications like gaming, artificial intelligence, and high-performance computing. They work on hardware architecture, driver development, and parallel computing optimizations to maximize performance. GPU Engineers collaborate with software developers, hardware designers, and researchers to improve graphics rendering, machine learning acceleration, and computational efficiency.

What are the key skills and qualifications needed to thrive as a GPU engineer?

To thrive as a GPU Engineer, you need strong knowledge of computer architecture, proficiency in C/C++, and experience with parallel programming models such as CUDA or OpenCL, along with a degree in computer science, electrical engineering, or a related field. Familiarity with debugging tools, driver development, performance profiling utilities, and hardware simulation platforms is typically required. Excellent problem-solving abilities, attention to detail, and effective teamwork and communication skills help distinguish top candidates. These skills ensure that GPU Engineers can develop high-performance solutions, efficiently troubleshoot hardware and software issues, and collaborate successfully in multidisciplinary environments.

What are some common challenges faced by GPU engineers, and how are they addressed?

GPU Engineers often face challenges such as optimizing code for maximum parallel efficiency, debugging complex hardware-software interactions, and keeping pace with rapidly evolving GPU architectures. Addressing these issues typically requires a combination of deep architectural understanding, use of specialized profiling and debugging tools, and ongoing collaboration with hardware, software, and QA teams. Many companies provide ongoing training and encourage knowledge sharing within engineering teams to help individuals stay current and effectively tackle new technical hurdles. Overcoming these challenges not only sharpens technical expertise but also opens doors for career growth into architect, team lead, or principal engineer roles.

How much does a GPU engineer make?

The average salary for a GPU engineer varies depending on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually. Senior roles or those with specialized skills in graphics processing, parallel computing, or CUDA programming can earn higher salaries. Compensation may also include bonuses, stock options, and benefits based on the employer and geographic region.
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Gpu Engineer jobs near you
Infographic showing various Gpu Engineer job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $101,752 per year, or $48.9 per hour.

GPU Engineer

Houston, TX • On-site

Bot Auto
See more jobs at Bot Autoexternal

Full-time

Posted 23 days ago

Job description

Company Introduction

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.

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