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Gpu Jobs in Michigan (NOW HIRING)

$153K - $204K/yr

The Runtime & GPU Systems team builds and operates secure, high-performance environments for multi-tenant Kubernetes platforms at scale. Our team sits at the intersection of container runtimes ...

$182K - $242K/yr

If you're excited about supporting bleeding-edge bare metal GPU environments, this is the team to join. About the Role: As a Bare Metal Support Engineer, you'll operate and support CoreWeave ...

$96K - $132K/yr

THE ROLE As a Senior Failure Analysis Engineer, you will play a critical role in ensuring the reliability, performance, and successful deployment of AMD's next-generation GPU-accelerated server ...

Orchestrate compute workloads across cloud and bare-metal GPU clusters * Design systems for secure, fault-tolerant deployment and observability * Build internal tooling to accelerate developer ...

Drive GPU-accelerated computing strategies, optimizing performance across compute, storage, and networking layers * Partner cross-functionally with hardware, algorithms, and product teams to deliver ...

Linux administration fundamentals, compute (CPU/GPU), high-speed networking, shared/parallel storage concepts, and capacity/performance planning.* Automation/scripting (e.g., Bash/Python) and ...

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How much do gpu jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for gpu in Michigan is $47.89, according to ZipRecruiter salary data. Most workers in this role earn between $47.16 and $56.59 per hour, depending on experience, location, and employer.

What is a GPU?

A GPU, or Graphics Processing Unit, is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images and graphics for display. While originally developed for rendering graphics in video games and visual applications, GPUs are now widely used for parallel processing tasks in areas such as artificial intelligence, data science, and scientific computing. Their architecture allows them to handle thousands of operations simultaneously, making them much faster than traditional CPUs for certain workloads.

What is a GPU engineer?

A GPU job refers to a computing task that utilizes a Graphics Processing Unit (GPU) for acceleration. GPUs are specialized processors designed for parallel processing, making them ideal for tasks like machine learning, scientific simulations, and rendering. Many software applications offload intensive computations to GPUs to improve performance and efficiency. Jobs related to GPUs can involve programming, optimization, and hardware configuration in fields like AI, gaming, and data analysis.

What are the key skills and qualifications needed to thrive as a GPU engineer?

To thrive as a GPU Engineer, you need a solid background in computer engineering, mathematics, and programming languages such as C++ or CUDA, often supported by a relevant degree. Familiarity with GPU architectures, parallel computing frameworks, and tools like OpenCL or Vulkan is typically required. Analytical thinking, problem-solving, and teamwork are essential soft skills for innovating and debugging complex systems. These abilities are crucial for optimizing performance, ensuring compatibility, and driving advancements in graphics and computational workloads.

What are some common challenges faced by GPU engineers when optimizing performance for various applications?

GPU engineers often encounter challenges such as balancing high computational throughput with power efficiency, ensuring compatibility across different hardware architectures, and optimizing code for parallel processing. They must also troubleshoot bottlenecks in memory bandwidth and latency that can impact performance. Collaboration with software developers and hardware architects is crucial to identify and resolve these issues, and staying updated with the latest advances in GPU technologies is essential for continued success.

What is the difference between Gpu vs Data Scientist?

AspectGpuData Scientist
Required CredentialsKnowledge of parallel computing, programming skills (CUDA, OpenCL)Degree in Computer Science, Statistics, or related fields; programming skills
Work EnvironmentHardware-focused, technical, often in R&D or engineering teamsData analysis, modeling, research in various industries
Industry UsageTech, gaming, AI, machine learningFinance, healthcare, tech, marketing

Gpu specialists focus on hardware and parallel processing for computing tasks, while data scientists analyze data to extract insights. Both roles require technical skills, but Gpu roles are more hardware-oriented, whereas data scientists focus on data analysis and modeling.

How to get into the graphics processing unit industry?

To enter the GPU industry, candidates typically need a strong background in computer engineering, electrical engineering, or computer science, with skills in programming languages like C++ and knowledge of graphics APIs such as DirectX or Vulkan. Relevant experience can be gained through internships, projects, or certifications in hardware design, GPU architecture, or related fields. Staying updated on industry developments and obtaining certifications like NVIDIA's or AMD's developer programs can also enhance job prospects.

What are the most commonly searched types of Gpu jobs in Michigan?

The most popular types of Gpu jobs in Michigan are:

What are popular job titles related to Gpu jobs in Michigan?

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

What cities in Michigan are hiring for Gpu jobs?

Cities in Michigan with the most Gpu job openings:

Infographic showing various Gpu job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 77% Physical, 7% Hybrid, and 16% Remote job distribution, with an average salary of $99,607 per year, or $47.9 per hour.

Senior ML Accelerator Engineer - GPU

General Motors

Warren, MI • On-site

$170K - $258K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 5 days ago


Key responsibilities

  • Design, implement, benchmark, and iterate on CUDA-based kernels and custom operators to optimize on-vehicle inference workloads.

  • Build and improve tooling and infrastructure for profiling, debugging, and validating CUDA kernels and accelerator-backend code.

  • Partner with AI Solutions, Compilers, and Architecture teams to translate model and system requirements into kernel roadmaps and project plans.


General Motors rating

8.2

Company rating: 8.2 out of 10

General Motors

Based on 308 frontline employees who took The Breakroom Quiz

7.3

Company rating compared to similar companies: 7.3 out of 10

Automakers average

Based on 6,331 frontline employees who took The Breakroom Quiz


Job description

Job Description

About the Mission
GM's vision of Zero Crashes, Zero Emissions, and Zero Congestion guides everything we do in autonomous and assisted driving. The AV organization is building advanced automated driving technologies, including Level 4-capable fully self-driving systems, to move us toward safer, more sustainable, and more accessible mobility. For the AI Kernels & Compilers team, that mission shows up in the details: turning cuttingedge perception, prediction, and planning research into productiongrade software that can run efficiently and reliably on real vehicles at scale. We pioneer new approaches to model export, kernel development, and performance engineering so that every cycle on our accelerators translates into better situational awareness, faster reaction times, and more robust behavior on the road. If you want your compiler and kernels work to directly influence how automated vehicles understand and react to the world - while operating at the safety, reliability and scale of a company like GM - this is where that impact becomes real.
About the Team
The AI Kernels team builds highperformance GPU kernels and custom libraries that sit at the heart of our onvehicle ML inference for ADAS and autonomous driving. We own making core AI workloads faster, more reliable, and easier to maintain and deploy on real cars, under realworld constraints.
That means:

  • Designing and implementing custom operators when vendor libraries hit their limits
  • Integrating those kernels deep into our ML runtime stack
  • Debugging and tuning GPU performance across the AV software stack, often on hardwareintheloop
  • We partner closely with AI Solutions, AI Compilers, AI Architecture, and AI Tooling to ensure models deploy efficiently to the car while consistently meeting strict latency, throughput, and reliability targets. If you enjoy pushing GPUs to their limits and seeing your work directly impact how autonomous vehicles perceive and act in the world, this is the team for you.


What you'll be doing (Responsibilities)

  • Design, implement, benchmark, and iterate on CUDA-based kernels and custom operators to squeeze every last drop of performance out of on-vehicle inference workloads.
  • Build and improve tooling and infrastructure that make it easier to profile, debug, and validate CUDA kernels and accelerator-backend code across the AV stack.
  • Partner with AI Solutions, Compilers, and Architecture to translate model and system requirements into concrete kernel roadmaps, priorities, and project plans.
  • Collaborate with cross-functional teams (compiler, performance tooling, runtime, deployment solutions) to deliver reusable, reliable, high-performance libraries into production.
  • Maintain high technology standards, methodologies, processes, and guidelines for GPU kernel development and performance engineering through code review.
  • Manage relationships with internal customers to ensure our kernels and libraries meet real-world needs

Your Skills & Abilities (Required Qualifications)

  • Minimum 2+ years of relevant industry experience or equivalent experience
  • BS, MS or PhD in CS, or related technical field
  • Excellent GPU programming skills in CUDA, with a thorough understanding of parallel programming patterns and GPU architecture.
  • Hands-on experience benchmarking, profiling, debugging and optimizing accelerator libraries and kernels to extract optimal performance using the NSight suite of tools or similar.
  • Strong background in software architecture, library design, and design patterns.
  • Strong C++ programming skills with the ability to feel comfortable in large codebases.
  • Solid background in system performance, high performance computing and/or architecture-aware optimizations.
  • Strong communication skills and the ability to work collaboratively within a team
  • Excellent analytical and problem-solving skills


What Will Give You A Competitive Edge (Preferred Qualifications)

  • 2+ years of relevant industry experience or equivalent experience
  • Experience with tensor core programming, CUTLASS and/or CuTe
  • Experience with ML model architectures, in particular transformer-based
  • Experience with low latency or real time systems
  • Experience with lower levels of an accelerator software stack (i.e. drivers, runtimes, and compilers)

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

  • The salary range for this role: is$170,100 to $258,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
  • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. The selected candidate will be required to travel <25% for this role. This job may be eligible for relocation benefits.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.


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About General Motors

Sourced by ZipRecruiter

General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908