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Cuda Programmer Jobs in Texas (NOW HIRING)

... GPUs, CUDA programming, and NCCL, including performance benchmarking via MLPerf. • Deep familiarity with storage hardware (HDDs, SSDs, NVMe), enclosures, and specialized appliances like Network ...

Senior Software Engineer, CUTLASS Kernels

Austin, TX · On-site

$121K - $160K/yr

Experience with CUDA, OpenCL, HIP, SYCL, Mojo, Pallas, Triton, Mosaic, Halide, or any general-purpose or domain-specific programming language targeting highly parallel accelerators. * Deep ...

Coordinate CUDA ↔ OpenGL interoperability for real-time visualization Required Qualifications ... Experience with multi-threaded programming and async execution models * Experience with 3D point ...

$100K - $137K/yr

Familiarity with highly parallel programming frameworks such as CUDA, Metal or OpenCL Direct experience in computer vision is not required!

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How much do cuda programmer jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for cuda programmer in Texas is $36.83, according to ZipRecruiter salary data. Most workers in this role earn between $23.94 and $47.93 per hour, depending on experience, location, and employer.

What are the most common challenges faced by cuda programmers in their daily work?

Cuda Programmers often encounter challenges related to optimizing code performance and efficiently managing memory on GPU architectures. Debugging and profiling can be complex, as issues may arise from both the code and hardware-specific elements, requiring close attention to parallelization and bottlenecks. Collaboration is key, as you’ll typically work closely with software engineers, data scientists, or researchers to integrate and optimize code for specialized workflows. Successfully navigating these challenges helps drive significant performance improvements and innovation in high-performance computing applications.

What are the key skills and qualifications needed to thrive as a cuda programmer?

To thrive as a Cuda Programmer, you need strong programming skills in C/C++ and parallel computing, with a solid understanding of GPU architectures and CUDA development. Familiarity with CUDA libraries, performance profiling tools, and platforms like NVIDIA Nsight or Visual Studio is often required, while certifications from NVIDIA can be advantageous. Problem-solving abilities, attention to detail, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can optimize complex algorithms, work efficiently on high-performance computing projects, and collaborate smoothly with multidisciplinary teams.

What is a cuda programmer?

A CUDA Programmer develops high-performance parallel computing applications using NVIDIA's CUDA (Compute Unified Device Architecture) framework. They optimize algorithms to run efficiently on GPUs, accelerating tasks such as machine learning, scientific simulations, and real-time data processing. This role requires proficiency in C/C++, an understanding of GPU architectures, and experience with parallel computing concepts to maximize performance.

What are the most commonly searched types of Cuda Programmer jobs in Texas? The most popular types of Cuda Programmer jobs in Texas are:
What job categories do people searching Cuda Programmer jobs in Texas look for? The top searched job categories for Cuda Programmer jobs in Texas are:
Infographic showing various Cuda Programmer job openings in Texas as of July 2026, with employment types broken down into 92% Full Time, 3% Part Time, 2% Temporary, 1% Contract, and 2% Nights. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $76,614 per year, or $36.8 per hour.

Senior HPC Storage Engineer

NVIDIA

Austin, TX • On-site

Full-time

Re-posted 20 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies


Job description

Job Summary:
NVIDIA has been transforming computer graphics and accelerated computing for over 25 years, now focusing on AI to define the next era of computing. As a Senior HPC Storage Engineer, you will lead the research, design, and implementation of innovative storage solutions for high performance computing workloads, while collaborating with teams to optimize infrastructure performance and resource utilization.
Responsibilities:
• Research and analyze existing internal distributed storage services.
• Research, design, and implement scalable, next-gen distributed storage services for HPC workloads, optimizing both performance and cost-effectiveness to meet NVIDIA’s growing infrastructure needs
• Develop tooling to automate management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources.
• Detail the general procedures and practices, perform technology evaluations, related to distributed file systems.
• Collaborate across teams to better understand developers' workflows and capture their infrastructure requirements.
• Influence and guide methodologies for building, testing, and deploying applications to ensure efficient performance and resource utilization.
• Supporting our researchers to run their flows on our clusters including performance analysis and optimizations of deep learning workflows
• Root cause analysis and suggest corrective action for problems large and small scales
Qualifications:
Required:
• Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience.
• 8+ years of experience designing and/or operating large scale storage infrastructure.
• Experience analyzing and tuning storage performance for a variety of workloads.
• Proficient in Centos/RHEL and/or Ubuntu Linux distros including Python programming and bash scripting
• In depth understanding of container technologies like Docker, Enroot
Preferred:
• Extensive experience with parallel and distributed filesystems (Ceph, Weka.io, Vast, Lustre, GPFS) and Linux storage kernel development.
• Proficient with NVIDIA GPUs, CUDA programming, and NCCL, including performance benchmarking via MLPerf.
• Deep familiarity with storage hardware (HDDs, SSDs, NVMe), enclosures, and specialized appliances like Network Appliance.
• Strong background in Software Defined Networking (SDN) and high-performance networking for AI/HPC clusters.
• Practical experience applying industry-standard frameworks, specifically PyTorch and TensorFlow.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Nvidia employees say

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Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993