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Cuda Programmer Jobs (NOW HIRING)

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch . You will work on the GPU performance layer powering large-scale ...

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch . You will work on the GPU performance layer powering large-scale ...

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch . You will work on the GPU performance layer powering large-scale ...

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch . You will work on the GPU performance layer powering large-scale ...

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch . You will work on the GPU performance layer powering large-scale ...

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch . You will work on the GPU performance layer powering large-scale ...

NVIDIA is seeking outstanding senior engineers to work on the CUDA driver, a key component of accelerated GPU computing. You will join a versatile software engineering team that delivers innovative ...

Senior DL Compiler Engineer- CUDA Tile

Austin, TX

$121.40K - $160.10K/yr

We are hiring software engineers for the CUDA Tile team. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models ...

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch . You will work on the GPU performance layer powering large-scale ...

CUDA-Q is the open-source programming framework bridging classical accelerated computing and quantum processors, to enable fault-tolerant quantum-GPU supercomputing. This role sits where quantum ...

OR

$122.40K - $161.30K/yr

We are hiring software engineers for the CUDA Tile team. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models ...

Senior DL Compiler Engineer- CUDA Tile

Redmond, WA

$137.20K - $180.90K/yr

We are hiring software engineers for the CUDA Tile team. NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models ...

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Cuda Programmer information

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How much do cuda programmer jobs pay per hour?

As of May 29, 2026, the average hourly pay for cuda programmer 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.

What is a CUDA Programmer job?

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 key skills and qualifications needed to thrive in the Cuda Programmer position, and why are they important?

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 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 cities are hiring for Cuda Programmer jobs? Cities with the most Cuda Programmer job openings:
What are the most commonly searched types of Cuda Programmer jobs? The most popular types of Cuda Programmer jobs are:
What states have the most Cuda Programmer jobs? States with the most job openings for Cuda Programmer jobs include:
Infographic showing various Cuda Programmer job openings in the United States as of May 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 100% In-person job distribution, with an average salary of $82,234 per year, or $39.5 per hour.

CUDA Kernel Engineer

PRAGMATIKE

Chicago, IL • Remote

Full-time

Medical, Dental, Vision, Retirement

Posted 26 days ago


Job description

Location: Remote US
Start date: ASAP
Languages: English (required)

About the Role

Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital, founded by MIT CSAIL researchers.

We are searching for a CUDA Kernel Engineer who has hands-on experience developing and optimizing NVIDIA CUDA kernels from scratch. You will work on the GPU performance layer powering large-scale, high-throughput AI systems used by Fortune 500 customers.

This role is ideal for someone who deeply understands NVIDIA GPU architecture, memory hierarchy, warp-level execution, and profiling workflowsnot someone coming from generic hardware, FPGA, or non-NVIDIA compute backgrounds. You will directly influence the GPU efficiency, throughput, and scalability of mission-critical AI systems.

What Youll Do

  • Design, implement, and optimize custom CUDA kernels for NVIDIA GPUs, with a focus on maximizing occupancy, memory throughput, and warp efficiency.
  • Profile GPU workloads using tools such as Nsight Compute, Nsight Systems, nvprof, and CUDA‐MEMCHECK.
  • Analyze and eliminate performance bottlenecks including warp divergence, uncoalesced memory access, register pressure, and PCIe transfer overhead.
  • Improve GPU memory pipelines (global, shared, L2, texture memory) and ensure proper memory coalescing.
  • Collaborate closely with AI systems, model acceleration, and backend distributed systems teams.
  • Contribute to GPU architecture decisions, kernel libraries, and internal performance-engineering best practices.

What Were Looking For

  • Proven track record building NVIDIA CUDA kernels from scratchnot just calling existing libraries.
  • Strong ability to optimize kernels (tiling strategies, occupancy tuning, shared memory design, warp scheduling).
  • Deep understanding of CUDA threads, warps, blocks, and grids, GPU memory hierarchy and memory coalescing, as well as warp divergence (how to detect, analyze, and mitigate it)
  • Experience diagnosing PCIe bottlenecks and optimizing host-device transfers (pinned memory, streams, batching, overlap).
  • Familiarity with C++, CUDA runtime APIs, and GPU debugging/profiling tooling.

Bonus Points

  • Experience with multi-GPU or distributed GPU systems (NCCL, NVLink, MIG).
  • Background in GPU acceleration for ML frameworks or HPC workloads.
  • Knowledge of model inference optimization (TensorRT, CUDA Graphs, CUTLASS).
  • Exposure to compiler-level optimization or PTX/SASS analysis.
  • Startup experience or comfort working in fast-moving, ambiguous environments.

Why This Role Will Pivot Your Career

  • Research pedigree: MIT CSAIL founders recognized for breakthrough AI and systems contributions.
  • Customer impact: Deploy AI solutions powering Fortune 500 clients.
  • Industry momentum: Lab alumni have led high-value acquisitions (MosaicML Databricks, Run:AI Nvidia, W&B CoreWeave).
  • Funding & growth: Oversubscribed seed round, next funding in 2026.
  • Career growth & influence: Lead AI initiatives, optimize pipelines, and directly impact production AI systems at scale.
  • Culture & autonomy: Own critical systems while collaborating with world-class engineers.
  • Aspirational impact: Solve GPU/AI performance challenges few engineers ever face.

Benefits

  • Competitive salary & equity options
  • Sign-on bonus
  • Health, Dental, and Vision
  • 401k

Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.