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Cuda Engineer Jobs in Michigan (NOW HIRING)

KLA

Algorithm Engineer (Image Processing)

Ann Arbor, MI · On-site

$105K - $180K/yr

Linear and Nonlinear Optimization techniques, CUDA/GPU Programming frameworks (e.g., Keras), and Data Analysis and Visualization tools * Having a strong understanding of innovative research in ...

Kla

Algorithm Engineer (Image Processing)

Ann Arbor, MI · Hybrid

$105K - $180K/yr

Linear and Nonlinear Optimization techniques, CUDA/GPU Programming frameworks (e.g., Keras), and Data Analysis and Visualization tools * Having a strong understanding of innovative research in ...

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 +1

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 ...

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All JobsCuda Engineer JobsCuda Engineer Jobs in Michigan

Cuda Engineer information

See Michigan salary details

$31.8K

$93.5K

$119.8K

How much do cuda engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for cuda engineer in Michigan is $93,506.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,100.00 and $118,500.00 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 are popular job titles related to Cuda Engineer jobs in Michigan?

For Cuda Engineer jobs in Michigan, the most frequently searched job titles are:

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

The top searched job categories for Cuda Engineer jobs in Michigan are:

What cities in Michigan are hiring for Cuda Engineer jobs?

Cities in Michigan with the most Cuda Engineer job openings:

Cuda Engineer jobs near you
Infographic showing various Cuda Engineer job openings in Michigan as of August 2026, with employment types broken down into 87% Full Time, 6% Part Time, 2% Temporary, 4% Contract, and 1% Nights. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $93,506 per year, or $45 per hour.

Senior Machine Learning Engineer (Computer Vision & AI)

faurecia S.A.

Auburn Hills, MI • On-site

$100 - $130/hr

Other

Posted 2 days ago

New

Job description

Forvia, a sustainable mobility technology leaderRole Summary

As a Senior Machine Learning Engineer, you will play a key role in developing and deploying advanced AI solutions that drive innovation across our automotive products and manufacturing processes. This role is focused on applied machine learning, with an emphasis on computer vision, predictive analytics, and scalable model deployment. You will partner with cross‑functional teams across engineering, manufacturing, and R&D to design, build, and productionize machine learning models that deliver measurable business impact. This is a hands‑on role requiring strong technical depth, ownership of model lifecycle, and the ability to operate effectively in a fast‑paced, evolving environment.

Key Responsibilities
  • Design, develop and deploy machine learning models with a focus on computer vision, predictive maintenance and anomaly detection
  • Build and maintain end‑to‑end ML pipelines, including data preprocessing, model training, evaluation and deployment
  • Collaborate with engineering, manufacturing and business stakeholders to translate real‑world problems into scalable AI solutions
  • Optimize model performance and scalability using GPU acceleration and parallel computing frameworks
  • Leverage Python and deep learning frameworks (PyTorch, TensorFlow) to implement production‑ready solutions
  • Partner with data and software engineering teams to integrate models into production systems and workflows
  • Contribute to AI innovation initiatives, including exploration of generative AI use cases in design and engineering contexts
  • Ensure best practices in model reproducibility, documentation and performance monitoring
  • Stay current with advancements in machine learning and apply relevant techniques to improve existing capabilities
Your Profile & Competencies
  • Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field
  • 5+ years (preferably 7+) of hands‑on experience in machine learning or applied AI roles
  • Strong expertise in machine learning and deep learning, with practical experience in computer vision applications
  • Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow
  • Experience building and deploying models in production environments
  • Familiarity with GPU acceleration (CUDA or similar frameworks) and performance optimization techniques
  • Experience with ML pipelines, model lifecycle management and scalable system design
  • Ability to work effectively in matrixed, cross‑functional environments
  • Strong problem‑solving and analytical skills, with the ability to translate complex data into actionable insights
  • Effective communicator, able to explain technical concepts to non‑technical stakeholders
  • Experience in automotive, manufacturing or industrial environments is a strong plus
  • Familiarity with cloud platforms (e.g., Azure) and Agile development practices is preferred
What we can do for you
  • We provide an engaging and dynamic environment where you can contribute to the development of sustainable mobility leading technologies.
  • Our company is the seventh‑largest global automotive supplier, offering ample opportunities for career development.
  • We welcome energetic and agile people who can thrive in a fast‑changing environment and share our strong values.
  • We cultivate a learning environment, dedicating tools and resources to ensure we remain at the forefront of mobility. Our people enjoy an average of more than 22 hours of online and in‑person training within FORVIA University.
  • We offer a multicultural environment that values diversity and international collaboration and have adopted gender diversity targets and inclusion action plans.
  • We are committed to achieving CO2 Net Zero. In June2022, Forvia became the first global automotive group to be certified with the new SBTI Net‑Zero Standard.
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