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Computer Vision Software Engineer Jobs in Michigan

Contract Software Engineer (Irl & US) Responsibilities: * Define, own and standardize the product ... computer vision, deep learning and sensor fusion with ultrasonics, radar and lidar * Ensure ...

... from computer vision applications to generative AI models. This position requires a strong ... The ideal candidate will be a versatile engineer who can navigate complex software development ...

... from computer vision applications to generative AI models. This position requires a strong ... The ideal candidate will be a versatile engineer who can navigate complex software development ...

Software Engineer

Orion, MI · On-site

$135K/yr

Bachelor's degree in Computer Science or Electrical Engineering * 3+ years of C# development ... Medical / Dental / Vision * Profit Sharing & Pension plans Responsibilities of the Software ...

Remote Software Engineer

Ann Arbor, MI

$50.75 - $69.50/hr

... computer vision, data visualization tools excellent written and verbal communication skills ... or software programming Spring boot, AWS, microservices, Docker, Jenkins, Github, Kubernates and ...

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Showing results 1-20

Computer Vision Software Engineer information

See Michigan salary details

$55.3K

$128.6K

$179.1K

How much do computer vision software engineer jobs pay per year?

As of Jun 20, 2026, the average yearly pay for computer vision software engineer in Michigan is $128,581.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $150,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Computer Vision Software Engineer, and why are they important?

To thrive as a Computer Vision Software Engineer, you need strong programming skills (particularly in Python or C++), a solid background in mathematics and algorithms, and a degree in computer science or a related field. Experience with deep learning frameworks (such as TensorFlow or PyTorch), OpenCV, and familiarity with computer vision libraries and cloud platforms is highly valuable. Creative problem-solving, attention to detail, and effective teamwork are standout soft skills in this role. These skills and qualities are crucial for developing, optimizing, and deploying innovative computer vision solutions that address real-world challenges.

What is the difference between Computer Vision Software Engineer vs Machine Learning Engineer?

AspectComputer Vision Software EngineerMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, Electrical Engineering, or related; knowledge of computer vision librariesBachelor's or Master's in CS, Data Science, or related; strong programming and statistical skills
Work EnvironmentDevelops algorithms for image/video analysis, often in tech, automotive, or healthcare industriesBuilds models for various data types, including images, text, and tabular data, across multiple industries
Employer & Industry UsageTech companies, autonomous vehicles, robotics, healthcareTech firms, finance, startups, research institutions

While both roles involve machine learning concepts, Computer Vision Software Engineers focus specifically on image and video data, developing algorithms for visual understanding. Machine Learning Engineers have a broader scope, working on various data types and models. The roles often overlap but differ mainly in their specialization and application areas.

What are some common challenges Computer Vision Software Engineers face when deploying models to production environments?

One frequent challenge for Computer Vision Software Engineers is optimizing models to run efficiently in production, especially on devices with limited processing power or memory. Additionally, ensuring that models remain robust when exposed to real-world data—which may differ significantly from training data—requires ongoing monitoring and potential retraining. Collaboration with data engineers and DevOps teams is often essential to streamline deployment pipelines and address issues like data drift or latency. Staying updated with rapidly evolving frameworks and hardware accelerators is also key for success in this role.

What are Computer Vision Software Engineers?

Computer Vision Software Engineers are professionals who design, develop, and implement software solutions that enable computers to interpret and process visual information from the world, such as images and videos. They use techniques from machine learning, artificial intelligence, and image processing to build applications like facial recognition, object detection, and autonomous vehicles. Their work often involves programming, working with large datasets, and optimizing algorithms for accuracy and speed. These engineers are crucial in industries ranging from healthcare and automotive to security and entertainment.
What are popular job titles related to Computer Vision Software Engineer jobs in Michigan? For Computer Vision Software Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Computer Vision Software Engineer jobs in Michigan look for? The top searched job categories for Computer Vision Software Engineer jobs in Michigan are:

Robotics Engineer, Perception/Computer Vision

Nastech Global

Warren, MI • On-site

Contractor

Posted 20 days ago


Job description

Position: Senior Robotics Engineer, Perception/Computer Vision

Location: Warren, Michigan

Duration: 12+Months with possible extensions

Main Skills: Senior Robotic AI-Perception Engineer (AI/ML, perception, computer vision, Python, TensorFlow and/or PyTorch)

About the Role:

We are seeking a Senior Robotics Engineer, Perception/Computer Vision to join our Advanced Development team within the Autonomous Robotics Center (ARC). In this role, you will develop perception features that enable robots with advanced capabilities such as object detection, obstacle avoidance, path optimization, and manipulation. This position combines artificial intelligence and computer vision techniques applied to real-world scenarios in dynamic manufacturing environments.

At ARC, we leverage advanced robotics, machine learning, and artificial intelligence to solve complex manufacturing challenges at unprecedented scale. Joining our organization provides the opportunity to work on cutting-edge technologies, contribute to innovation, and collaborate with a diverse team of experts. You will play a key role in advancing our automation capabilities and ensuring our robotic systems remain at the forefront of the industry.

Key Responsibilities:

  • Design, develop, and implement perception algorithms for segmentation, scene understanding, object detection and localization, classification, and dynamic tracking.
  • Integrate AI and computer vision algorithms with ROS (Robot Operating System) for real-time deployment on autonomous robots (e.g., mobile manipulators).
  • Design and maintain cloud-based pipelines for data collection, annotation, preprocessing, model training, and evaluation.
  • Collaborate with hardware engineers, software engineers, and domain experts to integrate with mapping, motion planning, and controls.
  • Develop offline tools to test and validate perception models in both simulation and real-world environments.
  • Stay updated with emerging technologies and best practices in robotic perception; lead and participate in academic and industrial collaborations.
  • Generate intellectual property, document results, and publish papers.

Required Qualifications:

  • Passion for robotics and a strong desire to accelerate the application of robotics with AI.
  • Master’s or Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field (or Bachelor’s degree with exceptional track record).
  • 3+ years of experience developing and deploying AI/ML, perception, and computer vision (e.g., mono and stereo cameras, RGB-D, event camera, LiDAR) on robotic systems.
  • Proficiency in Python or C++ with hands-on experience in deep learning frameworks such as TensorFlow and PyTorch.
  • Solid understanding of robotics fundamentals, perception and navigation methods (e.g., SLAM, planning), and their typical strengths and shortcomings.
  • Consistently seeks opportunities and embraces challenges to drive self-growth and improvement.

Preferred Qualifications:

  • Ph.D. in Computer Science, Machine Learning, Robotics, Computer Vision, or a related research field.
  • Hands-on robotics experience, such as autonomous vehicles (AV), ADAS, or industrial automation systems in manufacturing environments.
  • Experience with robotics frameworks such as ROS/ROS2 (e.g., Nav2, MoveIt).
  • Understanding of CI/CD pipelines and modern software development practices.