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Nvidia Engineering Jobs in Michigan (NOW HIRING)

Optimal Inc.

GPU Platform Infrastructure Engineer

Warren, MI · On-site

$100K - $131K/yr

... engineering workloads Experience with monitoring, observability, and reporting tools Strong scripting and automation skills using Python, Bash, or similar languages Familiarity with NVIDIA GPU ...

Utilidata

VP, AI & Applications

Ann Arbor, MI · On-site +1

$230K - $290K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... The VP partners with the VP, Engineering on the platform that runs these methods in production, and ...

Ford Motor Company

Software Engineer

Redford, MI · On-site

Experience: 3+ years of professional software engineering experience in a production environment ... Develop and optimize software to deploy machine learning models on edge devices (NVIDIA Jetson/Thor ...

Astemo Ltd

Embedded Software Engineer

Farmington Hills, MI · On-site

$129K - $170K/yr

Engineering Position Overview and Objective Astemo's Advanced Engineering team is hiring an ... Effective communication and presentation skills, with NVIDIA Drive OS and toolchain experience a ...

Astemo

Embedded Software Engineer

Farmington Hills, MI · On-site

$129K - $170K/yr

Engineering Position Overview and Objective Astemo's Advanced Engineering team is hiring an ... Effective communication and presentation skills, with NVIDIA Drive OS and toolchain experience a ...

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Nvidia Engineering information

See Michigan salary details

$40.5K

$128K

$151.7K

How much do nvidia engineering jobs pay per year?

As of Jun 12, 2026, the average yearly pay for nvidia engineering in Michigan is $128,009.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $150,800.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior engineers in specialized fields such as software, hardware, or systems engineering at major technology companies can earn $500,000 or more annually, often including bonuses, stock options, and other compensation. Achieving this level typically requires extensive experience, advanced skills, and sometimes leadership roles or executive responsibilities.

What are the key skills and qualifications needed to thrive in the Nvidia Engineering position, and why are they important?

To thrive in Nvidia Engineering, candidates typically need strong proficiency in computer engineering, software development, and a solid understanding of hardware architecture, often backed by a relevant degree such as Electrical Engineering or Computer Science. Familiarity with tools like CUDA, C/C++, Python, and version control systems, as well as experience with GPU programming, are highly valued, and certifications such as Nvidia's Deep Learning Institute credentials can enhance a candidate's profile. Excellent problem-solving, team collaboration, and communication skills set top performers apart in this role. These skills and qualifications enable engineers to contribute effectively to complex, innovative projects that drive Nvidia's technological advancements.

What is an Nvidia Engineering job?

An Nvidia Engineering job involves designing, developing, and optimizing hardware or software solutions in areas such as graphics processing, AI, and high-performance computing. Engineers at Nvidia work on cutting-edge technologies, including GPUs, deep learning frameworks, and system architecture. Roles vary from hardware design and verification to software development and AI research, depending on expertise. Strong skills in programming, computer architecture, and problem-solving are typically required.

Which engineers does NVIDIA hire?

NVIDIA hires a variety of engineers including hardware engineers, software engineers, AI and deep learning engineers, and systems engineers. Candidates typically need strong technical skills, experience with programming languages like C++ and Python, and knowledge of GPU architectures or AI frameworks. The company values innovation, collaboration, and relevant technical certifications or degrees in engineering or computer science.

Is it hard to get hired at NVIDIA?

Getting hired as an engineer at NVIDIA can be competitive due to the company's reputation and high standards. Candidates typically need strong technical skills, relevant experience, and a solid understanding of areas like GPU architecture, software development, or AI. The hiring process often involves multiple interviews and technical assessments.

What types of projects do Nvidia Engineers typically work on, and how is teamwork structured within the engineering department?

Nvidia Engineers commonly engage in projects related to GPU development, AI and deep learning solutions, software driver optimization, and next-generation hardware innovation. Project teams are often multidisciplinary, bringing together software, hardware, and systems engineers to collaborate closely on end-to-end product development. Engineers frequently work in agile, fast-paced environments, attend regular team stand-ups, and participate in cross-functional meetings. This collaborative structure fosters creativity, accelerates problem-solving, and ensures high-quality product delivery while offering team members exposure to diverse technologies and career growth opportunities.

How much do NVIDIA engineers get paid?

NVIDIA engineers' salaries vary based on experience, role, and location, but the average annual salary for software engineers at NVIDIA typically ranges from $100,000 to $150,000. Senior engineers and those with specialized skills in AI, graphics, or hardware may earn higher compensation, often including bonuses and stock options.
What are the most commonly searched types of Nvidia Engineering jobs in Michigan? The most popular types of Nvidia Engineering jobs in Michigan are:
What are popular job titles related to Nvidia Engineering jobs in Michigan? For Nvidia Engineering jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Nvidia Engineering jobs in Michigan look for? The top searched job categories for Nvidia Engineering jobs in Michigan are:
What cities in Michigan are hiring for Nvidia Engineering jobs? Cities in Michigan with the most Nvidia Engineering job openings:
Nvidia Engineering jobs near you
Infographic showing various Nvidia Engineering job openings in Michigan as of June 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 83% Physical, 8% Hybrid, and 9% Remote job distribution, with an average salary of $128,009 per year, or $61.5 per hour.
GPU Platform Infrastructure Engineer

GPU Platform Infrastructure Engineer

Optimal Inc.

Warren, MI • On-site

$100K - $131K/yr

Full-time

Posted 9 days ago

Job description

Job Title: GPU Platform Infrastructure Engineer

Job Summary

Support the GM ARC RTD team by building and maintaining the foundational GPU cluster platform infrastructure supporting shared AI/ML, simulation, and validation workloads. This role focuses on GPU access governance, resource allocation, scheduling policies, observability, and operational support for multi-tenant GPU environments including RTX 6000, A100, B200, and future systems.

Required Experience
3+ years of experience in Platform Engineering, Infrastructure Engineering, DevOps, or related field
Bachelor's or Master's degree in Systems Engineering, Computer Science, Computer Engineering, or related discipline

Responsibilities
Manage GPU cluster access provisioning, onboarding, permissions, and lifecycle management
Design and maintain GPU resource allocation policies, quotas, namespace isolation, and scheduling configurations
Develop GPU utilization dashboards, reporting, monitoring, and capacity tracking solutions
Create reusable job submission templates and onboarding documentation for ML, Isaac Sim simulation, and validation workloads
Support platform governance, operational continuity, infrastructure scalability, and CI/CD integration
Design and develop GUI-based tools for streamlined Docker development workflows
Collaborate with infrastructure, AI/ML, and engineering teams to support shared GPU operations

Required Skills
Experience with Linux, Kubernetes, Docker, and GPU infrastructure environments
Knowledge of workload scheduling, resource management, and multi-tenant platform operations
Experience supporting AI/ML, simulation, or GPU-intensive engineering workloads
Experience with monitoring, observability, and reporting tools
Strong scripting and automation skills using Python, Bash, or similar languages
Familiarity with NVIDIA GPU platforms, containerized compute environments, and infrastructure automation tools
Experience with CI/CD pipelines and cloud platforms such as AWS, Azure, or GCP is a plus
Experience with GUI development frameworks is a plus
Strong troubleshooting, documentation, and operational support skills