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Cuda Programming Jobs in Texas (NOW HIRING)

Nvidia

Senior DL Compiler Engineer -CUDA Tile

Austin, TX

$121K - $160K/yr

In this role, you will be working on CUDA Tile, a new tile-based programming model for our GPUs. CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA ( You will design and implement ...

Nvidia

Senior DL Compiler Engineer -CUDA Tile

Austin, TX

$121K - $160K/yr

In this role, you will be working on CUDA Tile, a new tile-based programming model for our GPUs. CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA ( You will design and implement ...

NVIDIA

Senior HPC Storage Engineer

Austin, TX · On-site

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

Nvidia

Senior Compiler Engineer - Rust GPU

Austin, TX

$121K - $160K/yr

Solid understanding of parallel programming models, GPU architectures, and CUDA programming. * Strong software design skills, including debugging, profiling, and benchmarking compilers and GPU ...

Nvidia

Senior GPU Compiler Development Engineer

Austin, TX

$121K - $160K/yr

Work with NVIDIA GPU Architecture and CUDA Programming model teams to build abstractions to expose new GPU features in portable and performant ways in PTX ISA. PTX Compiler (PTXAS) apart from ...

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How much do cuda programming jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for cuda programming in Texas is $50.64, according to ZipRecruiter salary data. Most workers in this role earn between $40.96 and $59.13 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.
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Cuda Programming jobs near you
Infographic showing various Cuda Programming job openings in Texas as of August 2026, with employment types broken down into 1% Internship, 79% Full Time, 14% Part Time, 1% Temporary, 4% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $105,333 per year, or $50.6 per hour.

CUDA Senior Developer ( Mathematical Mindset/ New Grads

Ktek

Dallas, TX • On-site

Full-time

Re-posted 22 days ago

Job description

Position/ TITLE: CUDA Developers Junior to senior & Lead Level ( Mathematical Mindset/ New Grads)
Location : New yOrk, NJ, Dallas TX, Florida
Open for Fulltime & Contract
Please share resumes at Chandra.reddy@ktekresourcing.com

Who are we looking For:
We are seeking talented individuals with 3 to 8 years of experience who are passionate about mathematics and eager to learn CUDA programming to join our innovative team. While previous CUDA experience is beneficial, it is not mandatory to prioritize strong mathematical abilities, analytical thinking, and enthusiasm for learning and growth in high-performance computing.
Key Responsibilities
Learn and apply CUDA programming principles to develop and optimize GPU-accelerated applications.
Good team player who will work with team to contribute to design. He will work to implement, and debug parallel algorithms.
Analyze performance bottlenecks and optimize computations for maximum efficiency.
Document code, algorithms, and procedures clearly for internal and external stakeholders.
Technical Skills Must Have
Strong mathematical foundation in areas such as linear algebra, calculus, numerical methods, or statistics.
Proficiency in at least one programming language (C++, Python, or similar).
Excellent problem-solving skills and logical reasoning capabilities.
Ability to learn quickly and adapt to new technologies.
Technical Skills - Good to have
Familiarity with parallel computing concepts.
Exposure to GPU programming (CUDA/OpenCL).
Having Worked in Cuda Frameworks like RAPIDS, cuDF, cuTensor, PyTorch, TensorFlow is a plus.
Experience with scientific computing, numerical simulation and/or linear programming.
What We Offer
Opportunity to gain expertise in cutting-edge CUDA technology.
Supportive learning environment with mentorship from experienced CUDA developers.
Competitive salary and benefits.
Flexible working conditions (including remote work options).
Mphasis is an equal-opportunity employer. We value diversity and encourage candidates from all backgrounds to apply.
Application
Interested candidates should submit their resume and a brief statement highlighting their mathematical expertise, programming skills, and interest in CUDA development.
Please apply along with your answer to the following problem. Any application without an answer to the problem will not be entertained.
Mathematical Challenge:
Include your proposed approach or insights on the following linear algebra problem in your application:
'Given a very large sparse matrix, propose an efficient algorithm or method to quickly identify if the matrix is singular or invertible without performing full matrix inversion.'
Preferred Qualifications:
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
A portfolio showcasing CUDA experience.
Process Skills:
General SDLC processes
Understanding of utilizing Agile and Scrum software development methodologies
Skill in gathering and documenting user requirements and writing technical specifications.
Behavioral Skills:
Work closely with designers, Architects, data scientists, product managers, and other engineers to deliver comprehensive solutions.
Strong problem-solving skills, with a creative approach to tackling complex challenges.
Communicate effectively and share technical knowledge with the team.
Be open to feedback and continuously learn and adapt to new technologies.
Ability to work independently and as part of a team.
Passion for learning and staying updated on the latest technologies.
Good Attitude and Quick learner .
Certification (Good to have) :
Related to CUDA any certifications
AI/ML or Python certification.