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Mobile Slam Engineer Jobs (NOW HIRING)

Optimal Inc.

Robotics Engineer - AMR

Warren, MI · On-site

Robotics Engineer - Autonomous Mobile Robotics (AMR) Position Summary We are seeking a highly ... Mobile Robot (AMR) platforms using ROS/ROS2. * Develop and enhance SLAM algorithms by implementing ...

Grenzebach

Software Engineer

Newnan, GA · On-site

Software Engineer - Autonomous Mobile Robotics Location: Newnan, GA 30265 Benefits * FREE Employee ... Implement and maintain SLAM navigation algorithms. * Develop and maintain software using CODESYS ...

GRENZEBACH CORPORATION

Software Engineer

Newnan, GA · On-site

Software Engineer Join the Grenzebach Team Grenzebach Corporation is a high-tech company focusing ... mobile robotics, or warehouse automation systems * Experience implementing or supporting SLAM-based ...

GRENZEBACH

Software Engineer

Newnan, GA · On-site

Software Engineer Join the Grenzebach Team Grenzebach Corporation is a high-tech company focusing ... mobile robotics, or warehouse automation systems * Experience implementing or supporting SLAM-based ...

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How much do mobile slam engineer jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for mobile slam engineer in the United States is $60.14, according to ZipRecruiter salary data. Most workers in this role earn between $45.67 and $78.37 per hour, depending on experience, location, and employer.

What is a mobile SLAM engineer?

A Mobile SLAM Engineer is a professional who specializes in developing and implementing Simultaneous Localization and Mapping (SLAM) algorithms for mobile devices such as smartphones, tablets, or robots. SLAM is a technology that enables devices to map their environment and track their location in real-time, which is essential for applications like augmented reality, robotics, and autonomous navigation. Mobile SLAM Engineers work on optimizing these algorithms for resource-constrained platforms, ensuring they run efficiently and accurately on mobile hardware. Their work often involves software development, sensor integration, and testing in real-world environments.

What are the key skills and qualifications needed to thrive as a mobile SLAM engineer?

To thrive as a Mobile SLAM Engineer, you need a strong background in computer vision, robotics, and mathematics, typically supported by a relevant engineering or computer science degree. Expertise in programming languages such as C++ and Python, along with proficiency in SLAM frameworks (e.g., ORB-SLAM, RTAB-Map) and experience with tools like ROS and OpenCV, is commonly required. Strong problem-solving skills, adaptability, and effective communication help you collaborate across interdisciplinary teams and tackle complex technical challenges. These skills and qualifications are crucial for developing robust, real-time localization and mapping solutions essential to mobile robotics and AR/VR applications.

What are some common challenges mobile SLAM engineers face when deploying algorithms on resource-constrained devices?

Mobile SLAM Engineers often encounter challenges such as optimizing algorithm efficiency to run in real-time on devices with limited processing power and memory. Balancing accuracy and computational load is crucial, as robust SLAM performance can be resource-intensive. Additionally, engineers must address issues like sensor noise, environmental variability, and battery consumption, all while ensuring reliable localization and mapping. Close collaboration with hardware teams and software optimization specialists is often necessary to overcome these challenges.

What is the difference between Mobile Slam Engineer vs Mobile App Developer?

AspectMobile Slam EngineerMobile App Developer
Primary FocusOptimizing mobile ad campaigns and integrating ad solutionsDesigning, developing, and maintaining mobile applications
Required SkillsMobile advertising platforms, SDK integration, performance analysisProgramming languages (Swift, Java), UI/UX design, app development frameworks
Work EnvironmentAd tech companies, marketing agencies, mobile app companiesSoftware development firms, startups, tech companies
CertificationsMobile advertising certifications, SDK proficiencyMobile development certifications, programming courses

While both roles work within the mobile industry, a Mobile Slam Engineer specializes in optimizing mobile ad campaigns and integrating ad solutions, whereas a Mobile App Developer focuses on creating and maintaining mobile applications. The roles differ in their core responsibilities but often collaborate within the same industry environment.

What cities are hiring for Mobile Slam Engineer jobs?

Cities with the most Mobile Slam Engineer job openings:

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The most popular types of Slam Engineer jobs are:

What states have the most Mobile Slam Engineer jobs?

States with the most job openings for Mobile Slam Engineer jobs include:

What are popular job titles related to Mobile Slam Engineer jobs?

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

Mobile Slam Engineer jobs near you

Robotics Engineer - AMR

Warren, MI • On-site

Optimal Inc.
51 - 200 employees
Learn more about Optimal Inc.external

Contractor

Re-posted 6 days ago

Job description

Robotics Engineer - Autonomous Mobile Robotics (AMR)


Position Summary
We are seeking a highly skilled Robotics Engineer to support the development and deployment of next-generation Autonomous Mobile Robot (AMR) systems. This role focuses on advancing autonomous navigation, localization, mapping, and system integration using ROS/ROS2, AI-driven perception, and multi-sensor fusion technologies.
The ideal candidate will have strong experience in robotic software development, autonomous navigation, SLAM, and ROS integration, with the ability to develop and integrate intelligent robotic systems in industrial environments. A Master's degree in Robotics or a related field is preferred.

Key Responsibilities

  • Design, develop, and deploy software for Autonomous Mobile Robot (AMR) platforms using ROS/ROS2.
  • Develop and enhance SLAM algorithms by implementing inertial odometry fusion techniques to improve localization accuracy, efficiency, and robustness in challenging industrial environments.
  • Design and implement multi-map fusion methods to integrate data from multiple sensor modalities into a unified mapping framework for enhanced localization, navigation, and path planning.
  • Develop and integrate AI-based perception and navigation algorithms for autonomous robotic systems.
  • Integrate robotic software with LiDAR, cameras, IMUs, wheel encoders, and other sensing technologies.
  • Develop benchmarking and system integration tools to evaluate internal robotic platforms and commercial off-the-shelf solutions, enabling data-driven system architecture and performance analysis.
  • Integrate ROS with industrial automation systems, including PLC-controlled and standalone robotic environments.
  • Develop, test, validate, and optimize robotic software for real-world industrial deployment.
  • Troubleshoot hardware, software, and communication issues across robotic systems.
  • Collaborate with cross-functional engineering teams to deliver scalable and reliable autonomous robotic solutions.

Required Qualifications

  • Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science, or a related field.
  • Strong experience developing software using ROS/ROS2.
  • Experience with Autonomous Mobile Robots (AMRs) or mobile robotic platforms.
  • Strong understanding of SLAM, localization, sensor fusion, mapping, and autonomous navigation.
  • Experience integrating AI/ML algorithms into robotic perception or navigation systems.
  • Experience integrating LiDAR, cameras, IMUs, and other robotic sensors.
  • Experience with industrial automation and PLC integration is a plus.
  • Proficiency in C++ and Python.
  • Strong debugging, testing, and system integration skills.

Preferred Qualifications

  • Experience with navigation frameworks such as Nav2 and localization packages including AMCL.
  • Experience with motion planning, path planning, obstacle avoidance, and autonomous navigation.
  • Experience with sensor fusion frameworks (Kalman Filter, Extended Kalman Filter, factor graph optimization, or similar).
  • Experience with Gazebo, Isaac Sim, or other robotics simulation environments.
  • Experience deploying robotics solutions in manufacturing, warehouse automation, or industrial environments.

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