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Autonomous Driving Engineer Jobs in Michigan (NOW HIRING)

Pentangle Tech

Software Engineers

Southfield, MI · On-site

* Drive the concept design, prototyping, engineering, testing, release and enhancements of a cutting edge compute platform for Autonomous Driving * Work closely with other teams to ensure a seamless ...

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Wayve

Machine Learning Engineer, App SW

Detroit, MI · Hybrid

$283K - $381K/yr

You'll design and deliver ML-driven behaviors that scale from assisted to autonomous driving. Your ... Mentor senior engineers and shape the long-term technical direction across Autonomy. About you: In ...

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Autonomous Driving Engineer information

See Michigan salary details

$51.4K

$119.7K

$171.3K

How much do autonomous driving engineer jobs pay per year?

As of Jul 4, 2026, the average yearly pay for autonomous driving engineer in Michigan is $119,678.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $170,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Autonomous Driving Engineer position, and why are they important?

To thrive as an Autonomous Driving Engineer, you need strong expertise in robotics, computer vision, sensor fusion, and machine learning, generally backed by a relevant engineering or computer science degree. Familiarity with programming languages like Python or C++, frameworks such as ROS (Robot Operating System), and simulation tools like CARLA or MATLAB is typically required. Problem-solving, teamwork, and clear communication are important soft skills that help you excel when debugging complex systems and collaborating with multidisciplinary teams. These skills ensure the ability to develop innovative autonomous driving solutions that are safe, efficient, and effective in real-world environments.

What are some common challenges Autonomous Driving Engineers face on the job?

Autonomous Driving Engineers often work on highly complex systems where integrating hardware and software, ensuring sensor reliability, and maintaining safety standards can pose significant challenges. Collaborating across teams—such as hardware engineers, data scientists, and software developers—is a daily part of the role, requiring strong coordination and flexibility. Debugging scenarios in both real-world and simulated environments, handling vast datasets, and keeping up with rapidly evolving technology are also regular parts of the job. These challenges make the work both demanding and rewarding, offering continual learning and professional growth opportunities.

What is an Autonomous Driving Engineer job?

An Autonomous Driving Engineer develops software, algorithms, and systems that enable vehicles to drive autonomously. They work on perception, sensor fusion, path planning, and control systems using AI, computer vision, and robotics. Their role involves testing and refining autonomous systems in simulations and real-world environments to ensure safety and reliability.

What are the most commonly searched types of Autonomous Driving Engineer jobs in Michigan? The most popular types of Autonomous Driving Engineer jobs in Michigan are:
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Autonomous Driving Engineer jobs near you
Can we discuss the role of Autonomous Driving Vehicle Perception Engineer

Can we discuss the role of Autonomous Driving Vehicle Perception Engineer

INA Solution Inc

Northville, MI • On-site

Full-time

Posted 23 days ago

Be an early applicant

Job description

Job Title: Autonomous Driving Vehicle Perception Engineer

Location: Northville, MI (Onsite)

Duration: Full Time

What You will Do:

  • Design and implement advanced perception algorithms for autonomous vehicles using LiDAR, cameras, radar, and GNSS.
  • Develop and optimize sensor fusion techniques to combine data from multiple sensors, improving the accuracy and reliability of perception systems.
  • Create algorithms for object detection, tracking, semantic segmentation, and classification from 3D point clouds (LiDAR) and camera data.
  • Work on Simultaneous Localization and Mapping (SLAM) algorithms, including Graph SLAM, LIO-SAM, and visual-inertial SLAM.
  • Develop sensor calibration techniques (intrinsic and extrinsic) and coordinate transformations between sensors.
  • Participate in real-time systems design and optimization to meet the high-performance requirements of autonomous driving.
  • Work with ROS2 for integration and deployment of perception algorithms.
  • Develop, test, and deploy machine learning models for perception tasks such as object detection and segmentation.
  • Collaborate with cross-functional teams, including software engineers, data scientists, and hardware teams, to deliver end-to-end solutions.
  • Stay up-to-date with industry trends and emerging technologies to innovate and improve perception systems.

What You Will Bring:

  • Minimum 3+ years of experience in sensor calibration, multi-sensor fusion, or related domains.
  • Strong foundation in linear algebra, 3D geometry, coordinate frames, quaternions, probability, Bayesian filtering, and data association.
  • Hands-on experience with intrinsic and extrinsic calibration of LiDAR, cameras, and radar, including geometric calibration, coordinate transforms, and sensor synchronization.
  • Proven experience with perception algorithms for autonomous systems, particularly in the areas of LiDAR, camera, radar, GNSS, or other sensor modalities.
  • Deep understanding of LiDAR technology, point cloud data structures, and processing techniques; experience with PCL or Open3D.
  • Proficiency in sensor fusion for combining data from LiDAR, camera, radar, and GNSS, including handling time synchronization and motion distortion.
  • Solid background in computer vision techniques; experience with OpenCV and object detection models such as YOLO, Faster R-CNN, or SSD.
  • Experience with deep learning frameworks (TensorFlow or PyTorch) for object detection and segmentation tasks.
  • Hands-on experience with multi-object tracking algorithms such as SORT, DeepSORT, Kalman Filters, UKF, IMM, or JPDA.
  • Strong programming skills in C++ and Python; familiarity with geometric optimization libraries.
  • Familiarity with ROS2 for perception-based autonomous systems development.
  • Experience with parallel computing for real-time performance optimization (e.g., CUDA, OpenCL).