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Cuda Programmer 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 ...

... 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 ...

Algorithm Engineer

Ann Arbor, MI · On-site

$105K - $180K/yr

Linear and Nonlinear Optimization techniques,Statistical Models,CUDA/GPU Programming frameworks, and Data Analysis and Visualization tools * Great teammate with excellent written and verbal ...

Algorithm Engineer

Ann Arbor, MI · On-site

$105K - $180K/yr

Linear and Nonlinear Optimization techniques, Statistical Models, CUDA/GPU Programming frameworks, and Data Analysis and Visualization tools * Great teammate with excellent written and verbal ...

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 Programmer information

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How much do cuda programmer jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for cuda programmer in Michigan is $34.46, according to ZipRecruiter salary data. Most workers in this role earn between $22.40 and $44.86 per hour, depending on experience, location, and employer.

What is a cuda programmer?

A CUDA Programmer develops high-performance parallel computing applications using NVIDIA's CUDA (Compute Unified Device Architecture) framework. They optimize algorithms to run efficiently on GPUs, accelerating tasks such as machine learning, scientific simulations, and real-time data processing. This role requires proficiency in C/C++, an understanding of GPU architectures, and experience with parallel computing concepts to maximize performance.

What are the key skills and qualifications needed to thrive as a cuda programmer?

To thrive as a Cuda Programmer, you need strong programming skills in C/C++ and parallel computing, with a solid understanding of GPU architectures and CUDA development. Familiarity with CUDA libraries, performance profiling tools, and platforms like NVIDIA Nsight or Visual Studio is often required, while certifications from NVIDIA can be advantageous. Problem-solving abilities, attention to detail, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can optimize complex algorithms, work efficiently on high-performance computing projects, and collaborate smoothly with multidisciplinary teams.

What are the most common challenges faced by cuda programmers in their daily work?

Cuda Programmers often encounter challenges related to optimizing code performance and efficiently managing memory on GPU architectures. Debugging and profiling can be complex, as issues may arise from both the code and hardware-specific elements, requiring close attention to parallelization and bottlenecks. Collaboration is key, as you’ll typically work closely with software engineers, data scientists, or researchers to integrate and optimize code for specialized workflows. Successfully navigating these challenges helps drive significant performance improvements and innovation in high-performance computing applications.

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

The most popular types of Cuda Programmer jobs in Michigan are:

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

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

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

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

Infographic showing various Cuda Programmer job openings in Michigan as of August 2026, with employment types broken down into 76% Full Time, 15% Part Time, 8% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $71,675 per year, or $34.5 per hour.

Autonomous Driving Vehicle Perception Engineer

Northville, MI • On-site

Reveille Technologies
51 - 200 employees

Other

Posted 20 days ago


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