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Map Localization Jobs in Michigan (NOW HIRING)

Map the user journey throughout their interactions with the organization * Define how users ... Manage translators and localization specialists * Understand entire ecosystem of services including ...

... localization, natural language processing, and conversational AI. They automate and optimize the ... classification, terrain mapping, intelligent document processing, and AI-powered agent ...

Machine Learning Engineer

Dearborn, MI · On-site

$105K - $126K/yr

... localization, natural language processing, and conversational AI. * They automate and optimize the ... mapping, intelligent document processing, and AI-powered agent workflows * Train, fine-tune, and re ...

Map the user journey throughout their interactions with the organization * Define how users ... Manage translators and localization specialists * Understand entire ecosystem of services including ...

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Map Localization information

What is the difference between Map Localization vs GIS Technician?

AspectMap LocalizationGIS Technician
Required CredentialsGPS, GIS, or mapping software certificationsGIS certifications, degree in geography or related field
Work EnvironmentFieldwork, outdoor mapping, mobile devicesOffice-based, desktop GIS software
Employer & Industry UsageNavigation apps, autonomous vehicles, outdoor mappingUrban planning, environmental management, utilities
Search & Comparison IntentUnderstanding field mapping rolesTechnical GIS data management

Map Localization focuses on real-time positioning and navigation, often in outdoor or mobile environments, using GPS and mapping tools. GIS Technicians handle spatial data analysis, map creation, and GIS software management primarily in office settings. While both roles involve geographic data, Map Localization emphasizes field-based positioning, whereas GIS Technicians focus on data processing and map development.

What is map localization?

Map localization is the process of determining a device's or vehicle’s precise position within a known map or environment. It is a crucial component in robotics, autonomous vehicles, and navigation systems, allowing them to understand their location relative to their surroundings. Accurate map localization enables systems to navigate safely, avoid obstacles, and perform tasks efficiently. This process often uses sensors like GPS, LiDAR, cameras, and algorithms such as SLAM (Simultaneous Localization and Mapping).

What are some common challenges faced by professionals working in map localization roles?

Professionals in map localization often encounter challenges such as managing the accuracy of real-time data from multiple sources and ensuring that maps remain up-to-date with constantly changing environments. Additionally, working with large volumes of geospatial data requires strong analytical and technical skills, especially when integrating information from LiDAR, GPS, and camera systems. Collaboration with cross-functional teams, such as software developers and robotics engineers, is essential to solve localization issues and to deliver reliable navigation solutions. Staying current with advances in localization algorithms and mapping technologies is also important for ongoing success in this field.

What are the key skills and qualifications needed to thrive as a Map Localization Engineer, and why are they important?

To thrive as a Map Localization Engineer, you need a strong background in robotics, computer vision, and algorithms, often supported by a degree in computer science, electrical engineering, or a related field. Proficiency with tools and frameworks such as ROS (Robot Operating System), SLAM (Simultaneous Localization and Mapping), and programming languages like C++ and Python is typically required. Strong problem-solving skills, attention to detail, and effective communication are essential soft skills for collaborating on complex projects and debugging localization systems. These skills are crucial for developing accurate and reliable localization solutions that enable autonomous navigation and mapping in real-world environments.
What are popular job titles related to Map Localization jobs in Michigan? For Map Localization jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Map Localization jobs in Michigan look for? The top searched job categories for Map Localization jobs in Michigan are:
What cities in Michigan are hiring for Map Localization jobs? Cities in Michigan with the most Map Localization job openings:
Autonomous Driving Vehicle Perception Engineer

Autonomous Driving Vehicle Perception Engineer

INA Solution Inc

Northville, MI • On-site

Contractor

Posted 7 days ago

Be an early applicant


Job description

Job Title: Autonomous Driving Vehicle Perception Engineer

Location: Northville, MI (Onsite)

Experience: 4–10 Years

Duration: 12 months+

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).