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How much do slam engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for slam engineer in Michigan is $92,045.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,800.00 and $110,700.00 per year, depending on experience, location, and employer.

What is a slam engineer?

A SLAM (Simultaneous Localization and Mapping) Engineer develops algorithms and systems that enable machines, like robots or AR/VR devices, to map their environment while tracking their own position. They work with sensor fusion, computer vision, and machine learning to enhance real-time navigation and spatial awareness. This role is crucial in robotics, autonomous vehicles, and augmented reality applications. A SLAM Engineer typically has expertise in C++, Python, ROS, and technologies like LiDAR and visual odometry.

What are the main projects and responsibilities I can expect as a slam engineer?

As a SLAM Engineer, you'll typically be responsible for developing, optimizing, and integrating algorithms that enable robots or autonomous devices to navigate and map their environments. This may involve working with sensor data from LiDAR, cameras, or IMUs, implementing real-time data processing pipelines, and testing your solutions in both simulated and real-world scenarios. You’ll often collaborate closely with robotics hardware engineers, software developers, and research scientists to ensure reliable system performance. Additionally, you may participate in field deployments, debugging sessions, and ongoing enhancements to keep up with the latest research and industry trends.

What are the key skills and qualifications needed to thrive in the slam engineer position, and why are they important?

To thrive as a SLAM Engineer, you need expertise in robotics, computer vision, and probabilistic state estimation, usually supported by a degree in computer science, robotics, or electrical engineering. Familiarity with tools like ROS (Robot Operating System), C++/Python programming, and experience with libraries such as OpenCV, PCL, or GTSAM are typically required. Strong problem-solving ability, attention to detail, and effective teamwork are crucial soft skills in this position. These capabilities are vital for developing and maintaining robust simultaneous localization and mapping solutions, ultimately ensuring high-performance autonomous systems.

How much do slam engineers make?

Slam engineers typically earn a median annual salary ranging from $70,000 to $120,000, depending on experience, location, and industry. They often require knowledge of robotics, automation, and control systems, and may work in manufacturing, logistics, or research environments.

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

The most popular types of Slam Engineer jobs in Michigan are:

What are popular job titles related to Slam Engineer jobs in Michigan?

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

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

The top searched job categories for Slam Engineer jobs in Michigan are:

Slam Engineer jobs near you
Infographic showing various Slam Engineer job openings in Michigan as of August 2026, with employment types broken down into 87% Full Time, 6% Part Time, 2% Temporary, 4% Contract, and 1% Nights. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $92,045 per year, or $44.3 per hour.

Autonomous Driving Vehicle Perception Engineer

Reveille Technologies

Northville, MI • On-site

Other

Posted 12 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

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