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Cuda Engineer Jobs (NOW HIRING)

We're looking for a CUDA Engineer to write and optimise the low-level GPU code that powers our inference workloads: designing custom CUDA kernels, tuning performance across memory bandwidth and ...

CUDA Programmer Location: Waukesha, WI We are seeking a skilled CUDA Programmer to design, develop, and optimize high-performance applications on NVIDIA GPUs . The role focuses on accelerating ...

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 ...

CUDA Developer - Remote

Phoenix, AZ · 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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 Engineer information

See salary details

$36.5K

$107.3K

$137.5K

How much do cuda engineer jobs pay per year?

As of Aug 30, 2026, the average yearly pay for cuda engineer in the United States is $107,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $136,000.00 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.

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Cities with the most Cuda Engineer job openings:

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What job categories do people searching Cuda Engineer jobs look for?

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Infographic showing various Cuda Engineer job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $107,282 per year, or $51.6 per hour.

Full-time

Medical

Posted 6 days ago


Job description

Fuse Energy is an energy startup on a mission to make energy abundant and affordable, fast. We combine first-principles thinking with cutting-edge technology to build a radically better energy system.
We've raised over $200M from top-tier investors including Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, 20VC, Hummingbird and Collaborative Fund, alongside strategic angels including Nico Rosberg and GPs behind Meta, Revolut, Spotify and Uber.
We're building a fully integrated energy company: developing our own solar, batteries and other generation projects, building our own hardware, improving and developing grid infrastructure, trading power in real time, using AI across the business, and installing distributed energy in homes. By selling directly to consumers we cut out the middleman, lower costs and pass the savings on to our customers.
As data centres become one of the largest and fastest-growing sources of electricity demand, Fuse is expanding into high-performance compute infrastructure at the intersection of energy and AI. We're looking for a CUDA Engineer to write and optimise the low-level GPU code that powers our inference workloads: designing custom CUDA kernels, tuning performance across memory bandwidth and compute bottlenecks, and squeezing maximum throughput out of every GPU in our fleet, working at the level of SMs, warps and memory hierarchies.
Responsibilities
  • Write and optimise custom CUDA kernels for core transformer inference operations
  • Profile kernels to identify and eliminate bottlenecks in occupancy, memory throughput and warp divergence
  • Apply kernel fusion to reduce memory round-trips and launch overhead across inference pipelines
  • Optimise memory access patterns and manage the memory hierarchy for maximum bandwidth utilisation
  • Implement quantisation-aware kernels and mixed-precision arithmetic to reduce latency and memory footprint
  • Build and tune caching mechanisms for efficient autoregressive decoding
  • Tune kernel launch configurations for target GPU architectures
  • Benchmark kernels against existing baselines and drive measurable throughput and latency improvements
  • Write tests for CUDA code to catch performance and correctness regressions
  • Maintain internal CUDA libraries and contribute to team coding standards and documentation

Requirements
  • 4+ years writing production CUDA code, with a track record of shipping performance-critical kernels
  • Deep understanding of GPU microarchitecture: warps, occupancy, register pressure and memory hierarchy
  • Strong CUDA C++ skills, including streams and asynchronous execution
  • Hands-on experience profiling to diagnose compute-bound vs memory-bound bottlenecks
  • Experience with kernel fusion, memory coalescing and avoiding warp divergence
  • Experience writing quantised and mixed-precision kernels
  • Solid grasp of parallel algorithm design and numerical precision tradeoffs
  • Bonus: transformer/attention-style kernels or autoregressive decoding; building high-performance GPU libraries from scratch; HPC or latency-critical performance engineering; multi-GPU or multi-node kernel-level optimisation; comfortable reading PTX/SASS to validate kernel efficiency

Benefits
  • Competitive salary and eligibility for equity
  • Biannual bonus scheme
  • Fully expensed tech to match your needs
  • Private health insurance
  • Breakfast and dinner allowance for office-based employees

As we hire globally, benefits vary by location.