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Cuda Engineer Jobs in Michigan (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 · On-site

$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 ...

Torc Robotics

ML Engineer, I - App Engine

Ann Arbor, MI · On-site

... CUDA • Experience in the development of real-time distributed systems • Profound knowledge of C++ • Familiarity with machine learning technologies (e.g. PyTorch) • Experience with Linux ...

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 ...

May Mobility

Robotics Engineer II

Ann Arbor, MI

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 ...

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Cuda Engineer information

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$31.8K

$93.5K

$119.8K

How much do cuda engineer jobs pay per year?

As of Jul 29, 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 are CUDA Engineers?

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

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 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 July 2026, with employment types broken down into 3% As Needed, 62% Full Time, 5% Part Time, 18% Temporary, 2% Contract, and 10% Nights. Highlights an 90% Physical, 4% Hybrid, and 6% Remote job distribution, with an average salary of $93,506 per year, or $45 per hour.

Manager, Engineering - App Engine (CUDA)

Torc Robotics

Ann Arbor, MI • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago

Job description

About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team
The Application Engine team builds the middleware platform that powers the next generation of Torc's Level 4 autonomous trucking stack. Our mission is to provide a robust, efficient, and flexible environment for integrating and managing diverse deep learning models and processes. We enable scalable development workflows, consistent performance, and safety-compliant deployments across real-world and simulated environments. By owning the core application layer, the App Engine team provides the scaffolding that allows feature teams to efficiently develop, integrate, and deploy advanced autonomous driving capabilities. We partner closely with Perception, Planning, Systems, Validation, Hardware, and Safety to ensure reliability, determinism, and scalability in production.
About the Role
We are seeking a technically strong and people-focused Engineering Manager to lead our App Engine team. While this is not a hands-on coding role, deep technical expertise in GPU parallel computing, CUDA, and model deployment is essential. You will drive technical direction, prioritize execution, and grow a high-performing team responsible for building production-grade middleware. This role sits at the intersection of software engineering, ML frameworks, GPU optimization, and safety-critical integration. Success requires both the ability to lead and coach engineers, and the technical depth to guide design decisions and challenge assumptions.
What You'll Do
  • Lead and grow a team building the application framework that integrates deep learning models into Torc's autonomy stack.
  • Drive technical execution across key focus areas: CUDA optimization, GPU resource management, model conversion pipelines (PyTorch, TensorRT, ONNX), and real-time system integration.
  • Ensure reliability, determinism, and scalability across multi-sensor autonomous driving workloads.
  • Partner with cross-functional teams (Perception, Planning, Systems, Validation, Hardware, Safety) to align technical direction and integration priorities.
  • Mentor, coach, and develop engineers while cultivating a collaborative, high-trust team culture.
  • Manage execution and delivery, balancing near-term goals with long-term architectural vision.
  • Establish scalable processes for development, testing, and integration in a safety-critical environment.

What You'll Need to Succeed
  • Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Robotics, or a related technical field.
  • 3+ years of full-cycle people management experience.
  • Deep technical expertise with CUDA, GPU parallel computing, and inference optimization.
  • Strong proficiency in C++ and Linux-based development with knowledge of real-time systems.
  • Experience with ML frameworks (PyTorch, TensorRT, ONNX) and model deployment pipelines.
  • Proven leadership managing software engineering teams in complex, cross-functional environments.
  • Strong understanding of system-level integration and safety-critical requirements.
  • Ability to thrive in a fast-paced, dynamic, and highly collaborative environment.

Bonus Points
  • Hands-on leadership style - comfortable diving into technical discussions and design reviews.
  • Experience building or managing application/middleware frameworks for production AV or ADAS systems.
  • Familiarity with ISO 26262, ASPICE, or other regulated safety standards.
  • Background in distributed systems, high-performance computing, or large-scale data recording pipelines.

Work Location: For this position, we are open to hiring in Ann Arbor, MI, Blacksburg, VA, Fort Worth, TX office work locations in a hybrid capacity. We are also open to hiring Remote in the United States.
Perks of Being a Full-time Torc'r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures
  • AD+D and Life Insurance

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.
Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: 102810
Hiring Range for Job Opening
US Pay Range
$160,800-$193,000 USD

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