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Cuda Jobs in Michigan (NOW HIRING)

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 ...

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 ...

Automotive Controls Algorithm Engineer

Warren, MI · On-site

$78K - $101K/yr

... CUDA, OpenMP, etc.) - Experience in image/signal processing algorithm development and implementation - Demonstrated experience in automotive embedded system development. - Working knowledge of radar ...

... 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 ...

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 ...

Experience with CUDA and GPU processing techniques * Proficiency with hard example mining, active learning or dataset composition techniques * Experience calculating metrics for and evaluating ...

Experience with GPU computing (CUDA, ROCm) and modern AI frameworks (PyTorch, TensorFlow, etc.) * Familiarity with high-performance storage systems, networking, and data pipelines * Strong foundation ...

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Cuda information

See Michigan salary details

$97.2K

$179.5K

How much do cuda jobs pay per year?

As of Sep 8, 2026, the average yearly pay for cuda in Michigan is $174,763.00, according to ZipRecruiter salary data. Most workers in this role earn between $178,700.00 and $178,700.00 per year, depending on experience, location, and employer.

What is a CUDA developer?

A CUDA job typically involves developing, optimizing, and implementing parallel computing applications using NVIDIA's CUDA platform. CUDA (Compute Unified Device Architecture) enables developers to leverage the power of GPUs for high-performance computing tasks such as deep learning, simulations, and scientific computing. Professionals in this role often work with C, C++, or Python, using CUDA libraries and frameworks to accelerate processing. Strong knowledge of parallel programming, memory management, and GPU architecture is essential for success in this field.

What are some common challenges faced when working as a CUDA developer, and how can they be addressed?

CUDA Developers often encounter challenges such as debugging complex parallel code, optimizing memory usage, and ensuring compatibility across different GPU architectures. To address these, it's important to leverage profiling tools like NVIDIA Nsight to identify bottlenecks and inefficiencies. Collaborating closely with team members, such as data scientists and software engineers, can also help in resolving integration issues and achieving better performance. Staying updated with the latest CUDA Toolkit releases and best practices is key to overcoming these challenges and delivering robust GPU-accelerated applications.

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

To thrive as a CUDA Developer, you need strong programming skills in C/C++, a solid understanding of parallel computing concepts, and experience with GPU architectures. Familiarity with the CUDA toolkit, NVIDIA GPUs, and related profiling/debugging tools is typically required, and certifications in GPU programming can be advantageous. Analytical thinking, problem-solving, and effective communication are essential soft skills for optimizing code and collaborating with cross-functional teams. These skills are crucial for developing high-performance applications that leverage GPU acceleration, ensuring efficiency and innovation in compute-intensive fields.

What is the difference between Cuda vs GPU Developer?

AspectCudaGPU Developer
Required CredentialsKnowledge of CUDA programming, often with a background in computer science or engineeringExperience with GPU programming, CUDA, OpenCL, or similar; often requires a degree in computer science or related fields
Work EnvironmentPrimarily focused on developing and optimizing CUDA-based applications for NVIDIA GPUsDesigning, developing, and maintaining GPU-accelerated applications across various platforms and hardware
Industry UsageUsed mainly in high-performance computing, AI, and scientific research involving NVIDIA GPUsApplied across gaming, scientific computing, AI, and multimedia industries

In summary, CUDA is a specialized skill set focused on programming NVIDIA GPUs using CUDA, while a GPU Developer has a broader role that may include using various GPU programming tools and working across multiple platforms. CUDA is a subset of the skills a GPU Developer might possess, making them closely related but distinct roles.

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

The most popular types of Cuda jobs in Michigan are:

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

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

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

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

What cities in Michigan are hiring for Cuda jobs?

Cities in Michigan with the most Cuda job openings:

Infographic showing various Cuda job openings in Michigan as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution, with an average salary of $174,763 per year, or $84 per hour.

Autonomous Driving Vehicle Perception Engineer

Reveille Technologies

Northville, MI • On-site

Other

This job post has expired today. Applications are no longer accepted.


Job description

ONLY FULLTIME NO CONTRACT

Job Title: Autonomous Driving Vehicle Perception Engineer

Location: Northville, MI (Onsite)

Type: Full-time

About the Role

We are seeking an experienced Perception Engineer to design, build, and deploy real-time perception and multi-sensor fusion algorithms for next-generation autonomous driving systems across LiDAR, camera, radar, and GNSS modalities.

Key Responsibilities

  • Algorithms & Models: 3D Object Detection, Multi-Object Tracking, Semantic Segmentation, Machine Learning (PyTorch, TensorFlow, YOLO, Faster R-CNN, DeepSORT).

  • Localization & SLAM: Graph SLAM, LIO-SAM, Visual-Inertial SLAM, Point Cloud Processing (PCL, Open3D).

  • Sensor Fusion & Calibration: Intrinsic & Extrinsic Calibration, Multi-Sensor Fusion (LiDAR, Camera, Radar, GNSS), Coordinate Transformations, Time Synchronization.

  • System Integration & Optimization: ROS2, C++, Python, Real-Time Systems, Parallel Computing (CUDA, OpenCL).

Key Requirements
  • Experience: 3+ years in sensor calibration, multi-sensor fusion, or autonomous vehicle perception.

  • Core Fundamentals: Strong background in 3D geometry, coordinate frames, quaternions, probability, Bayesian filtering, and data association.

  • Tech Stack: High proficiency in C++ and Python; hands-on experience with ROS2 and computer vision libraries (OpenCV, PCL, or Open3D).

  • Deep Learning & Tracking: Experience with PyTorch/TensorFlow, object detection models (YOLO, Faster R-CNN), and tracking algorithms (Kalman Filters, DeepSORT, UKF).

  • Optimization: Familiarity with parallel computing platforms (CUDA/OpenCL) for real-time performance.

Thanks and Regards,

Praveenkumar