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Gpu Performance Engineer Jobs in Detroit, MI (NOW HIRING)

Algorithm Engineer

Ann Arbor, MI · Hybrid

$105K - $180K/yr

Linear and Nonlinear Optimization techniques, CUDA/GPU Programming frameworks (e.g., Keras), and ... performance incentive programs and eligibility for additional benefits including but not limited to ...

Algorithm Engineer

Ann Arbor, MI · On-site

$105K - $180K/yr

Linear and Nonlinear Optimization techniques, CUDA/GPU Programming frameworks (e.g., Keras), and ... performance incentive programs and eligibility for additional benefits including but not limited to ...

Coordinate and execute on-vehicle tests to validate performance of Autonomous Vehicle software in ... Experience with CUDA and GPU processing techniques * Proficiency with hard example mining, active ...

Coordinate and execute on-vehicle tests to validate performance of Autonomous Vehicle software in ... Experience with CUDA and GPU processing techniques * Proficiency with hard example mining, active ...

Showing results 41-60

Gpu Performance Engineer information

See Detroit, MI salary details

$10

$59

$97

How much do gpu performance engineer jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for gpu performance engineer in Detroit, MI is $59.50, according to ZipRecruiter salary data. Most workers in this role earn between $48.80 and $67.36 per hour, depending on experience, location, and employer.

What is a GPU performance engineer?

A GPU Performance Engineer is a specialist who analyzes, optimizes, and improves the performance of graphics processing units (GPUs). They work on identifying bottlenecks, optimizing code, and ensuring that GPU hardware and software deliver maximum efficiency and speed. Their role may involve working with drivers, firmware, and applications to enhance graphics and compute workloads. This job is essential in industries like gaming, AI, and high-performance computing where GPU efficiency directly impacts user experience and system performance.

What are some common challenges faced by a GPU performance engineer when optimizing graphics workloads?

GPU Performance Engineers often encounter challenges such as identifying performance bottlenecks within complex graphics pipelines, balancing resource utilization, and achieving optimal frame rates across diverse hardware configurations. They must use specialized profiling tools and collaborate closely with developers, driver engineers, and QA teams to address issues like memory bandwidth limitations or shader inefficiencies. Staying updated with rapidly evolving GPU architectures and optimizing for both current and next-generation hardware are also key aspects of the role.

What are the key skills and qualifications needed to thrive as a GPU performance engineer, and why are they important?

To thrive as a GPU Performance Engineer, you need a strong background in computer architecture, programming (C/C++), and a degree in computer science, electrical engineering, or a related field. Proficiency with GPU profiling tools (e.g., NVIDIA Nsight, AMD Radeon GPU Profiler), performance analysis frameworks, and parallel computing libraries like CUDA or OpenCL is typically required. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaborating with developers and debugging performance bottlenecks. These skills and qualities are essential for optimizing GPU performance, ensuring efficient software-hardware interaction, and delivering high-quality graphics or compute solutions.

What is the difference between Gpu Performance Engineer vs Gpu Hardware Engineer?

AspectGpu Performance EngineerGpu Hardware Engineer
Primary FocusOptimizing GPU performance, benchmarking, and tuning softwareDesigning, developing, and testing GPU hardware components
Required SkillsProgramming, performance analysis, GPU architecture knowledgeHardware design, circuit analysis, FPGA/ASIC experience
Work EnvironmentSoftware development teams, labs for testing performanceHardware labs, manufacturing facilities, R&D centers
Common CertificationsNone specific, often requires computer engineering or related degreesElectrical engineering, VLSI design certifications

The Gpu Performance Engineer primarily focuses on optimizing and testing GPU software performance, while the Gpu Hardware Engineer designs and develops the physical GPU components. Both roles require a strong background in computer engineering, but differ in their core responsibilities and work environments.

What are popular job titles related to Gpu Performance Engineer jobs in Detroit, MI?

For Gpu Performance Engineer jobs in Detroit, MI, the most frequently searched job titles are:

What job categories do people searching Gpu Performance Engineer jobs in Detroit, MI look for?

The top searched job categories for Gpu Performance Engineer jobs in Detroit, MI are:

What cities near Detroit, MI are hiring for Gpu Performance Engineer jobs?

Cities near Detroit, MI with the most Gpu Performance Engineer job openings:

Infographic showing various Gpu Performance Engineer job openings in Detroit, MI as of August 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $123,764 per year, or $59.5 per hour.

Senior Machine Learning Engineer (Computer Vision & AI)

Faurecia

Auburn Hills, MI • On-site

$115K - $152K/yr

Full-time

Re-posted 16 days ago


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


Faurecia rating

5.9

Company rating: 5.9 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

Forvia, a sustainable mobility technology leader We pioneer technology for mobility experience that matter to people. Your mission, roles and responsibilities Role 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 and competencies to succeed 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 At Forvia, you will find an engaging and dynamic environment where you can contribute to the development of sustainable mobility leading technologies

We are the seventh-largest global automotive supplier, employing more than 157,000 people in more than 40 countries which makes a lot of opportunity for career development. We welcome energetic and agile people who can thrive in a fast-changing environment. People who share our strong values.

Team players with a collaborative mindset and a passion to deliver high standards for our clients. Lifelong learners. High performers.

Globally minded people who aspire to work in a transforming industry, where excellence, speed, and quality count. 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 (five campuses around the world) We offer a multicultural environment that values diversity and international collaboration.

We believe that diversity is a strength. To create an inclusive culture where all forms of diversity create real value for the company, we have adopted gender diversity targets and inclusion action plans. Achieving CO2 Net Zero as a pioneer of the automotive industry is a priority: In June 2022, Forvia became the first global automotive group to be certified with the new SBTI Net-Zero Standard (the most ambitious standard of SBTi), aligned with the ambition of the 2015 Paris Agreement of limiting global warming to 1.5C

Three principles guide our action:use less, use betteranduse longer, with a focus on recyclability and circular economy. Why join us FORVIA is an automotive technology group at the heart of smarter and more sustainable mobility. We bring together expertise in electronics, clean mobility, lighting, interiors, seating, and lifecycle solutions to drive change in the automotive industry.

With a history stretching back more than a century, we are the 7th largest global automotive supplier, employing more than 157,000 people in 43 countries. You'll find our technology in around 1 out of 2 vehicles produced anywhere in the world. In June 2022, we became the 1st global automotive group to be certified with the SBTI Net-Zero Standard.

We have committed to reach CO2 Net Zero by no later than 2045. As technological innovation and the need for sustainability transform the automotive industry, we are ideally positioned to deliver solutions that will enhance the lives of road-users everywhere.


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