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Cuda Engineer Jobs in Atlanta, GA (NOW HIRING)

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 ...

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CUDA Developer - Remote

Atlanta, GA · 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

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

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 ...

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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 ...

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SoloPulse is seeking a talented Senior Software Engineer to join our dynamic and innovative ... Hands‑on experience with NVIDIA CUDA and GPU acceleration * Experience with secure, reliable ...

SoloPulse is seeking a talented Senior Software Engineer to join our dynamic and innovative ... Hands-on experience with NVIDIA CUDA and GPU acceleration * Experience with secure, reliable ...

SoloPulse is seeking a talented Senior Software Engineer to join our dynamic and innovative ... Hands-on experience with NVIDIA CUDA and GPU acceleration * Experience with secure, reliable ...

SoloPulse is seeking a talented Senior Software Engineer to join our dynamic and innovative ... Hands-on experience with NVIDIA CUDA and GPU acceleration * Experience with secure, reliable ...

Go & Python Developer

Atlanta, GA · On-site

$48.25 - $66.50/hr

Go & Python Developer Location: Atlanta, GA Required Skills: * Core Language & Runtime: Go (primary ... GPU compute (NVIDIA CUDA/DCGM, vllm, llm-d, Intel Level-Zero/ driver stack and SR-IOV)

We are seeking an experienced AI/ML Engineer with deep expertise in manufacturing systems and ... Optimize CUDA kernels and implement parameter-efficient training techniques for large-scale model ...

... CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton Experience with hosting computer vision model inference on NVIDIA DGX Spark. Understanding of FDA ...

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Cuda Engineer information

See Atlanta, GA salary details

$35.1K

$103.2K

$132.2K

How much do cuda engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for cuda engineer in Atlanta, GA is $103,168.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,100.00 and $130,800.00 per year, depending on experience, location, and employer.

What is a CUDA engineer?

CUDA Engineers are software developers who specialize in using NVIDIA's CUDA (Compute Unified Device Architecture) platform to write programs that run on Graphics Processing Units (GPUs). They optimize and accelerate computational tasks by parallelizing code, making use of GPUs’ capabilities for high-performance computing. CUDA Engineers often work in fields like machine learning, scientific computing, and graphics, where large amounts of data need to be processed quickly. Their expertise includes proficiency in C/C++, CUDA programming, and understanding GPU hardware and parallel computing concepts.

What are the key skills and qualifications needed to thrive as a CUDA engineer?

To thrive as a CUDA Engineer, you need a strong proficiency in C/C++ programming, parallel computing concepts, and deep knowledge of GPU architectures, often supported by a computer science or engineering degree. Experience with NVIDIA CUDA Toolkit, profiling/debugging tools, and sometimes certifications like NVIDIA DLI are highly valuable. Strong problem-solving, attention to detail, and effective communication skills help you optimize code and collaborate across teams. These skills ensure efficient development of high-performance GPU applications and successful project delivery in compute-intensive fields.

What are some common challenges faced by CUDA engineers when optimizing GPU-accelerated applications?

CUDA Engineers frequently encounter challenges such as managing memory effectively between the host and the device, optimizing kernel performance, and minimizing data transfer bottlenecks. Debugging parallel code can also be complex due to race conditions and the difficulty of reproducing timing-related bugs. Collaborating closely with software developers and data scientists is essential to ensure that GPU resources are leveraged efficiently and that the application's overall performance meets project goals.

What is the difference between Cuda Engineer vs GPU Developer?

AspectCuda EngineerGPU Developer
Required CredentialsBachelor's or Master's in Computer Science, Engineering, or related; knowledge of CUDA, C++, parallel programmingBachelor's or Master's in Computer Science, Engineering, or related; experience with GPU programming, CUDA, OpenCL
Work EnvironmentResearch labs, tech companies, hardware firms focusing on GPU accelerationSoftware development teams, gaming, AI, scientific computing sectors
Employer & Industry UsageHardware manufacturers, AI companies, high-performance computing firmsGame development, scientific research, machine learning applications

While both roles involve GPU programming and CUDA expertise, a Cuda Engineer primarily focuses on developing and optimizing CUDA-based solutions for hardware acceleration. In contrast, a GPU Developer works on broader GPU programming tasks, including application development across various platforms. The roles often overlap but differ in scope and specific focus areas.

What job categories do people searching Cuda Engineer jobs in Atlanta, GA look for?

The top searched job categories for Cuda Engineer jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Cuda Engineer jobs?

Cities near Atlanta, GA with the most Cuda Engineer job openings:

    Infographic showing various Cuda Engineer job openings in Atlanta, GA as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $103,168 per year, or $49.6 per hour.

    CUDA Software Engineer - Remote

    YO AI Labs

    Atlanta, GA • Remote

    $60 - $100/hr

    Full-time

    Posted 2 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.