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3D Lidar Segmentation Jobs (NOW HIRING)

Perform high-precision 3D instance labeling, semantic segmentation, and bounding box annotation on multi-sensor data (LiDAR, Camera, Radar, etc.). • Vectorized Map Annotation: Annotate and edit ...

Develop and optimize deep learning models for depth estimation, object detection, segmentation ... Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo)

Computer Vision AI & ML Engineer

San Mateo, CA · On-site

$127K - $150K/yr

... segmentation, tracking, and 3D scene understanding using multi-modal sensor data. • Build ... RGB-D, LiDAR, stereo). • Experience with data annotation tools, dataset management, and ...

Perform high-precision 3D instance labeling, semantic segmentation, and bounding box annotation on multi-sensor data (LiDAR, Camera, Radar, etc.). * Vectorized Map Annotation: Annotate and edit high ...

Perform high-precision 3D instance labeling, semantic segmentation, and bounding box annotation on multi-sensor data (LiDAR, Camera, Radar, etc.). * Vectorized Map Annotation: Annotate and edit high ...

... 3D representations of key driving routes using recorded vehicle data (camera, LiDAR, IMU, and GPS ... semantic segmentation * Experience with 3D Vision * Publication record in relevant venues (CVPR ...

... 3D representations of key driving routes using recorded vehicle data (camera, LiDAR, IMU, and GPS ... semantic segmentation * Experience with 3D Vision * Publication record in relevant venues (CVPR ...

Computer Vision AI & ML Engineer

San Mateo, CA · On-site

$127K - $149K/yr

Develop and optimize deep learning models for depth estimation, object detection, segmentation ... Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo)

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3D Lidar Segmentation information

What are some common challenges faced by professionals working in 3D LiDAR segmentation, and how are they typically addressed?

Professionals in 3D LiDAR segmentation often encounter challenges such as dealing with noisy or incomplete data, managing large-scale datasets, and ensuring accurate object classification in complex environments. These challenges are commonly addressed through advanced preprocessing techniques, robust machine learning algorithms, and leveraging high-performance computing resources. Collaboration with data engineers, software developers, and domain experts is also essential to refine segmentation models and improve overall system performance.

What are the key skills and qualifications needed to thrive as a 3D Lidar Segmentation Specialist, and why are they important?

To thrive as a 3D Lidar Segmentation Specialist, you need a strong background in computer vision, machine learning, and point cloud data processing, often supported by a degree in computer science, engineering, or related fields. Familiarity with tools such as Python, C++, ROS, and libraries like PCL and Open3D, as well as experience with deep learning frameworks (e.g., TensorFlow, PyTorch), is essential. Analytical thinking, attention to detail, and effective problem-solving are crucial soft skills for interpreting complex data and collaborating in multidisciplinary teams. These competencies ensure accurate scene understanding, efficient workflow, and the development of robust solutions for applications like autonomous vehicles and robotics.

What is 3D Lidar segmentation?

3D Lidar segmentation is the process of dividing or clustering raw Lidar point cloud data into meaningful parts or objects, such as vehicles, pedestrians, buildings, or vegetation. This technique is crucial for applications like autonomous driving, mapping, and robotics, where understanding the environment in three dimensions is essential. By segmenting the data, algorithms can better identify and track objects, enabling safer navigation and more detailed scene analysis.
More about 3D Lidar Segmentation jobs
What cities are hiring for 3D Lidar Segmentation jobs? Cities with the most 3D Lidar Segmentation job openings:
What states have the most 3D Lidar Segmentation jobs? States with the most job openings for 3D Lidar Segmentation jobs include:
Infographic showing various 3D Lidar Segmentation job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution.
Autonomous Driving Vehicle Perception Engineer

Autonomous Driving Vehicle Perception Engineer

Quest Global

Northville, MI • On-site

$80K - $100K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 13 days ago


Quest Global rating

7.4

Company rating: 7.4 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

243rd of 368 rated engineering


Job description

Job Requirements

Quest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the contributions of diverse individuals and their areas of expertise, we are able to solve problems better, faster. This multi-dimensional approach enables us to solve the most critical and large-scale challenges across the aerospace & defense, automotive, energy, hi-tech, healthcare, medical devices, rail and semiconductor industries.

We are looking for humble geniuses, who believe that engineering has the potential to make the impossible possible; innovators, who are not only inspired by technology and innovation, but also perpetually driven to design, develop, and test as a trusted partner for Fortune 500 customers. As a team of remarkably diverse engineers, we recognize that what we are really engineering is a brighter future for us all. If you want to contribute to meaningful work and be part of an organization that truly believes when you win, we all win, and when you fail, we all learn, then we're eager to hear from you. The achievers and courageous challenge-crushers we seek, have the following characteristics and skills

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).

Pay Range: $80,000-$100,000 a year

Compensation decisions are made based on factors including experience, skills, education, and other job-related factors, in accordance with our internal pay structure. We also offer a comprehensive benefits package, including health insurance, paid time off, and retirement plan.

Work Requirements: This role is considered an on-site position located in Northville, MI, USA

  • You must be able to commute to and from the location with your own transportation arrangements to meet the required working hours.  

Benefits

  • 401(k) matching
  • Dental insurance
  • Health insurance
  • Paid time off
  • Vision insurance
  • Employer paid Life Insurance, Short- & Long-Term Disability

Employment Type: FULL_TIME

What Quest Global employees say

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Benefits

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