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Cuda Programmer Salary Jobs (NOW HIRING)

Parsons

C++ / CUDA Signal Processing Engineer

Aberdeen, MD · On-site

$100K - $176K/yr

Parsons welcomes an exceptional Signal Processing Engineer skilled in C++ and CUDA programming to ... Salary Range: $100,900.00 - $176,600.00 We value our employees and want our employees to take care ...

Nvidia

Senior Software Engineer - CUDA Driver

Santa Clara, CA · On-site

$143K - $189K/yr

NVIDIA is seeking outstanding senior engineers to work on the CUDA driver, a key component of ... The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for ...

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How much do cuda programmer salary jobs pay per hour?

As of Jul 10, 2026, the average hourly pay for cuda programmer salary in the United States is $39.54, according to ZipRecruiter salary data. Most workers in this role earn between $25.72 and $51.44 per hour, depending on experience, location, and employer.
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Infographic showing various Cuda Programmer Salary job openings in the United States as of July 2026, with employment types broken down into 93% Full Time, 1% Part Time, 2% Temporary, 1% Contract, and 3% Nights. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $82,234 per year, or $39.5 per hour.
CUDA Senior Developer ( Mathematical Mindset/ New Grads

CUDA Senior Developer ( Mathematical Mindset/ New Grads

Ktek

Dallas, TX • On-site

Full-time

Re-posted 24 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.