ZipRecruiter

Log In

1

Cuda Programming Jobs in Michigan (NOW HIRING)

May Mobility

Robotics Engineer II

Ann Arbor, MI · On-site

Strong programming skills in C/C++/Python in a Linux environment * Functional proficiency with ... Experience with CUDA and GPU processing techniques * Proficiency with hard example mining, active ...

May Mobility

Robotics Engineer II

Ann Arbor, MI · On-site

Strong programming skills in C/C++/Python in a Linux environment * Functional proficiency with ... Experience with CUDA and GPU processing techniques * Proficiency with hard example mining, active ...

Torc Robotics

ML Engineer, II - App Engine

Ann Arbor, MI · On-site

$153K - $183K/yr

Bachelor's degree in Computer Engineering, Electrical Engineering, or Software Engineering ... Experience with TensorRT and CUDA * Experience in the development of real-time distributed systems

Utilidata

AI Infrastructure Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end ... C++, CUDA, Go, Rust a plus * Excellent communication skills and comfort working cross-functionally ...

Utilidata

AI Infrastructure Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end ... C++, CUDA, Go, Rust a plus * Excellent communication skills and comfort working cross-functionally ...

next page

Showing results 1-20

All JobsCuda Programming JobsCuda Programming Jobs in Michigan

Cuda Programming information

See Michigan salary details

$24

$47

$71

How much do cuda programming jobs pay per hour?

As of Jul 12, 2026, the average hourly pay for cuda programming in Michigan is $47.38, according to ZipRecruiter salary data. Most workers in this role earn between $38.37 and $55.29 per hour, depending on experience, location, and employer.

What is the salary of NVIDIA CUDA developer?

The salary of an NVIDIA CUDA developer typically ranges from $80,000 to $130,000 annually, depending on experience, location, and industry. Skilled CUDA programmers with advanced knowledge of parallel computing and GPU architecture tend to earn higher salaries.

What jobs use CUDA?

Jobs that use CUDA include roles such as GPU programmer, software developer, data scientist, and machine learning engineer, especially in fields like high-performance computing, artificial intelligence, and scientific research. These roles often require knowledge of parallel programming, C++, and GPU architecture, and involve developing or optimizing software to run efficiently on NVIDIA GPUs.

Are CUDA programmers in demand?

CUDA programmers are in high demand due to the growing use of GPU computing in fields like artificial intelligence, scientific research, and data processing. Skills in parallel programming, GPU architecture, and CUDA toolkit are highly valued, and job opportunities are expected to increase as these technologies expand across industries.

How much do CUDA engineers make?

CUDA engineers typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in parallel programming and GPU optimization can command higher salaries, especially in tech hubs or companies with advanced AI and high-performance computing needs.

What is the difference between Cuda Programming vs GPU Developer?

AspectCuda ProgrammingGPU Developer
Required CredentialsKnowledge of CUDA, C/C++, parallel computingKnowledge of GPU architecture, CUDA, OpenCL, C/C++
Work EnvironmentHigh-performance computing, scientific research, AIGraphics, gaming, scientific visualization, AI
Industry UsageTech companies, research labs, AI firmsGaming, entertainment, tech, research

While Cuda Programming focuses specifically on writing code using NVIDIA's CUDA platform for parallel processing, GPU Developers have a broader role that includes designing, optimizing, and implementing GPU-based solutions across various platforms and technologies. Both roles require knowledge of GPU architecture and programming languages like C/C++, but GPU Developers often work on a wider range of applications beyond CUDA-specific projects.

What are popular job titles related to Cuda Programming jobs in Michigan? For Cuda Programming jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Cuda Programming jobs in Michigan look for? The top searched job categories for Cuda Programming jobs in Michigan are:
What cities in Michigan are hiring for Cuda Programming jobs? Cities in Michigan with the most Cuda Programming job openings:
Cuda Programming jobs near you
High Performance Compute (HPC) Software Engineer - HPC SW Systems

High Performance Compute (HPC) Software Engineer - HPC SW Systems

KLA

Ann Arbor, MI • On-site

$169K - $200K/yr

Full-time

Re-posted 15 hours ago

Job description

Job Summary:
KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem, and they are seeking a High Performance Compute (HPC) Software Engineer. The role involves designing and optimizing HPC software for large-scale Linux clusters, collaborating with hardware teams, and contributing to system-level tooling and infrastructure engineering.
Responsibilities:
• Design, develop, and optimize HPC software running on large-scale Linux clusters, including distributed and parallel workloads (MPI, multithreading, GPU-accelerated pipelines, containerized workloads).
• Optimize application performance and power utilization across CPU, memory, storage, and network subsystem, with attention to throughput, latency, and scaling behavior.
• Develop and maintain system-level tooling for cluster bring-up, diagnostics, monitoring including component power usages, and health checks.
• Work closely with algorithms, systems and application teams to understand and translate workload characteristics into power-efficient HPC software solutions.
• Collaborate with hardware and systems teams to define HPC node, storage, and interconnect requirements based on software and algorithm needs.
• Understand and influence CPU/GPU selection, memory sizing, PCIe layout, NUMA behavior, and network topology to ensure optimal software performance.
• Participate in HW/SW co-debug activities, including performance bottlenecks, stability issues, and failure analysis.
• Understand rack-level integration of HPC systems, focusing on power, cooling, cabling, networking, and physical layout considerations.
• Understand data-center and lab constraints such as power budgets, thermal limits, network drops, and serviceability.
• Contribute to best practices, and design reviews for new platforms and refresh cycles.
• Act as a technical bridge between software, hardware, systems teams.
• Provide clear technical documentation covering software and system architecture, deployment flows, performance assumptions.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
• Strong experience developing HPC or systems software on Linux.
• Proficiency in Java and/or C++ and/or other system-level or performance-oriented languages.
• Hands-on experience with parallel computing (MPI, OpenMP, multithreading). Candidates with GPU computing (CUDA, ROCm, or equivalent) would be preferred.
• Solid understanding of HPC hardware fundamentals: CPUs, memory hierarchies, storage, networking (Ethernet / InfiniBand).
• Practical experience working with clusters, servers, or rack-scale systems in lab or production environments.
• Strong debugging skills across software, OS, and hardware boundaries.
Preferred:
• Experience with containerized HPC environments (Docker, Singularity/Apptainer, Kubernetes in HPC contexts).
• Familiarity with high-speed interconnects, storage architectures, and performance benchmarking.
• Exposure to rack integration, including cabling, power distribution, cooling, and system bring-up.
• Experience in semiconductor, manufacturing, or high-reliability systems environments.
• Ability to reason about system reliability, MTBF/MTBA, and failure modes in large compute installations.
Company:
Kla creates tools and services that promote innovation in the electronics industry. Founded in 1975, the company is headquartered in Milpitas, USA, with a team of 10001+ employees. The company is currently Late Stage.

Apply