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Cuda Jobs in Rochester, MI (NOW HIRING)

Pentangle Tech

Software Engineers

Southfield, MI · On-site

Programming on GPUs with CUDA and/or OpenCL * C++ programming experience * Experience in creating robust and efficient system architectures and complex hardware-software systems * Experience ...

General Motors

Senior ML Compiler Engineer

Warren, MI

$98K - $134K/yr

You'lljoin a group ofdeepcompiler, systems, and GPU engineerswho enjoyworking onhard problems,anddiving into MLIR/ONNXand CUDA/TensorRTinternals. We value clear thinking, strong engineering ...

OptechUs

Automotive Controls Algorithm Engineer

Warren, MI

$78K - $101K/yr

... CUDA, OpenMP, etc.) - Experience in image/signal processing algorithm development and implementation - Demonstrated experience in automotive embedded system development. - Working knowledge of radar ...

Wayve

Machine Learning Engineer, App SW

Detroit, MI · Hybrid

$283K - $381K/yr

C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices. * Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the ...

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Cuda information

See Rochester, MI salary details

$102.6K

$189.6K

How much do cuda jobs pay per year?

As of Jun 29, 2026, the average yearly pay for cuda in Rochester, MI is $184,560.00, according to ZipRecruiter salary data. Most workers in this role earn between $188,700.00 and $188,700.00 per year, depending on experience, location, and employer.

What are some common challenges faced when working as a CUDA Developer, and how can they be addressed?

CUDA Developers often encounter challenges such as debugging complex parallel code, optimizing memory usage, and ensuring compatibility across different GPU architectures. To address these, it's important to leverage profiling tools like NVIDIA Nsight to identify bottlenecks and inefficiencies. Collaborating closely with team members, such as data scientists and software engineers, can also help in resolving integration issues and achieving better performance. Staying updated with the latest CUDA Toolkit releases and best practices is key to overcoming these challenges and delivering robust GPU-accelerated applications.

What are the key skills and qualifications needed to thrive as a CUDA Developer, and why are they important?

To thrive as a CUDA Developer, you need strong programming skills in C/C++, a solid understanding of parallel computing concepts, and experience with GPU architectures. Familiarity with the CUDA toolkit, NVIDIA GPUs, and related profiling/debugging tools is typically required, and certifications in GPU programming can be advantageous. Analytical thinking, problem-solving, and effective communication are essential soft skills for optimizing code and collaborating with cross-functional teams. These skills are crucial for developing high-performance applications that leverage GPU acceleration, ensuring efficiency and innovation in compute-intensive fields.

What is the difference between Cuda vs GPU Developer?

AspectCudaGPU Developer
Required CredentialsKnowledge of CUDA programming, often with a background in computer science or engineeringExperience with GPU programming, CUDA, OpenCL, or similar; often requires a degree in computer science or related fields
Work EnvironmentPrimarily focused on developing and optimizing CUDA-based applications for NVIDIA GPUsDesigning, developing, and maintaining GPU-accelerated applications across various platforms and hardware
Industry UsageUsed mainly in high-performance computing, AI, and scientific research involving NVIDIA GPUsApplied across gaming, scientific computing, AI, and multimedia industries

In summary, CUDA is a specialized skill set focused on programming NVIDIA GPUs using CUDA, while a GPU Developer has a broader role that may include using various GPU programming tools and working across multiple platforms. CUDA is a subset of the skills a GPU Developer might possess, making them closely related but distinct roles.

What is a Cuda job?

A CUDA job typically involves developing, optimizing, and implementing parallel computing applications using NVIDIA's CUDA platform. CUDA (Compute Unified Device Architecture) enables developers to leverage the power of GPUs for high-performance computing tasks such as deep learning, simulations, and scientific computing. Professionals in this role often work with C, C++, or Python, using CUDA libraries and frameworks to accelerate processing. Strong knowledge of parallel programming, memory management, and GPU architecture is essential for success in this field.

What are CUDA developers?

CUDA developers are software engineers who specialize in using NVIDIA's CUDA (Compute Unified Device Architecture) platform to write programs that run on Graphics Processing Units (GPUs). Their primary focus is on parallel computing, optimizing algorithms to leverage GPU acceleration for tasks such as scientific computing, machine learning, and data processing. These professionals typically have strong skills in C, C++, and Python, and a solid understanding of GPU hardware. CUDA developers are in demand in industries that require high-performance computing solutions.
What are the most commonly searched types of Cuda jobs in Rochester, MI? The most popular types of Cuda jobs in Rochester, MI are:
What job categories do people searching Cuda jobs in Rochester, MI look for? The top searched job categories for Cuda jobs in Rochester, MI are:
Cuda jobs near you

Software Engineers

Pentangle Tech

Southfield, MI • On-site

Other

Posted 6 days ago

Job description

  • Drive the concept design, prototyping, engineering, testing, release and enhancements of a cutting edge compute platform for Autonomous Driving
  • Work closely with other teams to ensure a seamless and robust implementation
  • Employ and develop world class tools. Invent and create new technologies and solutions
  • Demonstrate effective communication skills

Must Haves:

  • 5+ years of demonstrated experience in full life cycle software development (concept to delivery)
  • Knowledge and experience on ADAS and/or Autonomous Driving systems
  • Programming on GPUs with CUDA and/or OpenCL
  • C++ programming experience
  • Experience in creating robust and efficient system architectures and complex hardware-software systems
  • Experience developing middleware platform solutions
  • Experience in component and system integration, testing and verification on system and vehicle level
  • Experience developing in Linux/QNX or similar operating systems
  • Bachelors Degree in the areas of Computer Engineering, Computer Science, Electrical Engineering