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Remote Cuda Developer Jobs (NOW HIRING)

YO AI Labs

CUDA Developer - Remote

New York, NY · Remote

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your ...

New

YO AI Labs

CUDA Software Engineer - Remote

New York, NY · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your ...

New

YO AI Labs

CUDA Engineering Expert - Remote

New York, NY · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your ...

New

Weekday AI

CUDA Engineering Expert

$80 - $100/hr

Apply CUDA, HIP, shader programming, or related kernel programming expertise to improve performance ... This is a fully remote role that can be completed on your own schedule. * Projects can be extended ...

Pragmatike

CUDA Kernel Engineer (Remote US)

San Francisco, CA · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

Remote US Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on ... We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing ...

YO AI Labs

GPU Programming Expert - Remote

New York, NY · Remote

$60 - $85/hr

GPU Programming Expert - Remote Job Type: Contractor Location: Remote Job Overview We are seeking ... Design, implement, and optimize GPU software using CUDA, WebGPU, or GLSL . * Profile and optimize ...

New

YO AI Labs

GPU Programmer - Remote

New York, NY · Remote

$60 - $85/hr

GPU Programmer - Remote Job Type: Contractor Location: Remote Job Overview We are seeking ... Design, implement, and optimize GPU software using CUDA, WebGPU, or GLSL . * Profile and optimize ...

New

Snarkify

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Proficient in GPU programming languages such as CUDA. * Strong understanding of computer ... A flexible and innovative remote work environment. * Room for continuous growth and development in ...

Snarkify

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Proficient in GPU programming languages such as CUDA. * Strong understanding of computer ... A flexible and innovative remote work environment. * Room for continuous growth and development in ...

Leidos

Software Engineer

San Diego, CA · On-site +1

$87K - $157K/yr

... ocean remote sensing, and high-performance computing . We're looking for a Software Engineer ... Translate and enhance existing code for GPU/CUDA acceleration and parallel/distributed execution.

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Remote Cuda Developer information

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$83.5K

$102.5K

$135.5K

How much do remote cuda developer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for remote cuda developer in the United States is $102,500.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $115,000.00 per year, depending on experience, location, and employer.

What is a remote CUDA developer?

A Remote CUDA Developer is a software engineer who specializes in using NVIDIA's CUDA (Compute Unified Device Architecture) platform to develop parallel computing applications, often for high-performance tasks like machine learning, scientific computing, or data analysis. They work remotely, collaborating with teams online rather than being physically present in an office. These developers write and optimize code to run efficiently on NVIDIA GPUs, enabling applications to process large amounts of data much faster than traditional CPU-only solutions.

What skills and qualifications are needed to thrive as a remote CUDA developer?

To thrive as a Remote CUDA Developer, you need strong proficiency in C/C++ programming, parallel computing concepts, and a solid understanding of GPU architecture, typically backed by a degree in computer science or a related field. Experience with NVIDIA CUDA toolkit, GPU debugging tools, and version control systems like Git is commonly required. Excellent problem-solving skills, self-motivation, and effective remote communication abilities help distinguish high performers in this role. These skills are vital for efficiently delivering high-performance computing solutions and collaborating seamlessly with distributed teams.

How does a remote CUDA developer typically collaborate with team members across different locations?

As a Remote CUDA Developer, you will frequently collaborate with cross-functional teams such as data scientists, software engineers, and product managers through virtual meetings, code reviews, and collaborative platforms like GitHub or GitLab. Clear communication and thorough documentation are essential since team members may be in different time zones. You can expect to participate in regular stand-ups, sprint planning, and peer programming sessions, ensuring alignment and smooth integration of your GPU-accelerated code into larger projects. Tools like Slack, Zoom, and project management platforms help maintain connectivity and workflow efficiency.

What is the difference between Remote Cuda Developer vs Remote Machine Learning Engineer?

AspectRemote Cuda DeveloperRemote Machine Learning Engineer
Required CredentialsCUDA programming certifications, computer science degreeMachine learning certifications, data science background
Work EnvironmentSoftware development, GPU optimizationModel development, data analysis
Industry UsageHigh-performance computing, gaming, AIAI, data science, predictive modeling

Remote Cuda Developers focus on GPU programming and optimization using CUDA, primarily in high-performance computing and AI applications. Remote Machine Learning Engineers develop and deploy machine learning models, often utilizing GPU resources but with a broader focus on data and algorithms. While both roles may involve GPU expertise, Cuda Developers specialize in low-level programming, whereas Machine Learning Engineers work on model development and deployment.

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What cities are hiring for Remote Cuda Developer jobs?

Cities with the most Remote Cuda Developer job openings:

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Remote Cuda Developer jobs near you
Infographic showing various Remote Cuda Developer job openings in the United States as of August 2026, with employment types broken down into 80% Full Time, 3% Part Time, and 17% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $102,500 per year, or $49.3 per hour.

CUDA Developer - Remote

YO AI Labs

New York, NY • Remote

Full-time

Posted 3 days ago

New

Job description

CUDA Engineering Expert

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your expertise in CUDA, C++, and GPU programming to analyze, optimize, and improve high-performance GPU kernels.

No prior AI experience is required.

Key Responsibilities

  • Analyze, profile, and optimize GPU kernels using CUDA and profiling tools.

  • Identify performance bottlenecks and develop targeted optimization strategies.

  • Refactor C++ and CUDA code for efficiency and maintainability.

  • Develop shader logic using GLSL and WebGPU.

  • Document optimization processes, findings, and performance improvements.

  • Contribute to GPU architecture and performance discussions.

  • Collaborate with remote, cross-functional teams.

Required Qualifications

  • Strong expertise in CUDA programming and GPU kernel optimization.

  • Advanced C++ development skills.

  • Hands-on experience with GLSL and WebGPU.

  • Experience using GPU profiling tools such as NVIDIA Nsight or similar.

  • Strong understanding of GPU performance and architecture.

  • Excellent analytical, problem-solving, and technical communication skills.

  • Ability to work effectively in a remote environment.

Preferred Qualifications

  • Experience with high-performance computing or GPU-accelerated applications.

  • Experience optimizing workloads across different GPU architectures.

  • Background in graphics, compute shaders, or AI/ML acceleration.