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Cuda Programming Jobs in Humble, TX (NOW HIRING)

Bot Auto

GPU Engineer

Houston, TX · On-site

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.

Bot Auto

GPU Engineer

Houston, TX

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.

Viridien

Scientific Software Developer

Houston, TX · Hybrid

Experience with UNIX / POSIX programming * Highly experienced in debugging / profiling /optimizing * Highly experienced with MPI, CUDA, or other type of parallel computing * Highly experienced in ...

Cgg

Scientific Software Developer

Houston, TX · Hybrid

Experience with UNIX / POSIX programming * Highly experienced in debugging / profiling /optimizing * Highly experienced with MPI, CUDA, or other type of parallel computing * Highly experienced in ...

Viridien

Scientific Software Developer

Houston, TX · Hybrid

Experience with UNIX / POSIX programming * Highly experienced in debugging / profiling /optimizing * Highly experienced with MPI, CUDA, or other type of parallel computing * Highly experienced in ...

CGG Services (U.S.) Inc.

Research Geophysicist

Houston, TX · On-site

$80 - $120/hr

Excellent coding skills with one or more programming languages, such as C/C++, CUDA, FORTRAN, Python, or OPENCL. Innovative mindset. Exceptional analytical and problem‑solving skills. Highly ...

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Cuda Programming information

See Humble, TX salary details

$24

$46

$70

How much do cuda programming jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for cuda programming in Humble, TX is $46.94, according to ZipRecruiter salary data. Most workers in this role earn between $37.98 and $54.81 per hour, depending on experience, location, and employer.

Are CUDA programmers in demand?

CUDA programmers are in high demand due to the growing need for high-performance computing in fields like artificial intelligence, scientific research, and data analysis. Skills in parallel programming, GPU architecture, and CUDA toolkit are highly valued by employers across technology, automotive, and research industries.

What is the difference between Cuda Programming vs GPU Developer?

AspectCuda ProgrammingGPU Developer
Required CredentialsKnowledge of CUDA, C/C++, parallel computingKnowledge of GPU architecture, CUDA, OpenCL, C/C++
Work EnvironmentHigh-performance computing, scientific research, AIGraphics, gaming, scientific visualization, AI
Industry UsageTech companies, research labs, AI firmsGaming, entertainment, tech, research

While Cuda Programming focuses specifically on writing code using NVIDIA's CUDA platform for parallel processing, GPU Developers have a broader role that includes designing, optimizing, and implementing GPU-based solutions across various platforms and technologies. Both roles require knowledge of GPU architecture and programming languages like C/C++, but GPU Developers often work on a wider range of applications beyond CUDA-specific projects.

What does a CUDA programmer do?

A CUDA programmer develops software that leverages NVIDIA's CUDA platform to perform parallel computing tasks on GPUs. They write and optimize code using languages like C++ and CUDA-specific libraries to accelerate applications in fields such as scientific computing, machine learning, and graphics processing.
What are popular job titles related to Cuda Programming jobs in Humble, TX? For Cuda Programming jobs in Humble, TX, the most frequently searched job titles are:
What cities near Humble, TX are hiring for Cuda Programming jobs? Cities near Humble, TX with the most Cuda Programming job openings:
Cuda Programming jobs near you
Infographic showing various Cuda Programming job openings in Humble, TX as of June 2026, with employment types broken down into 93% Full Time, 2% Part Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $97,629 per year, or $46.9 per hour.

GPU Engineer

Bot Auto

Houston, TX • On-site

Full-time

Posted 5 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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