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Lidar Annotation Jobs (NOW HIRING)

Computer Vision AI & ML Engineer

San Mateo, CA · On-site

$127K - $149K/yr

Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo). * Experience with data annotation tools, dataset management, and augmentation techniques. * Familiarity ...

ML Engineer

New York, NY · On-site +1

$170K - $185K/yr

... cargo X-rays, LiDAR), foundation vision-language models that convert raw sensor data into ... You'll primarily build the tooling and automation that powers our annotation, model training, and ...

ML Engineer

Manhattan, NY

$170K - $185K/yr

... cargo X-rays, LiDAR), foundation vision-language models that convert raw sensor data into ... You'll primarily build the tooling and automation that powers our annotation, model training, and ...

Computer Vision AI & ML Engineer

San Mateo, CA · On-site

$127K - $149K/yr

Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo). * Experience with data annotation tools, dataset management, and augmentation techniques. * Familiarity ...

Data Annotator

San Francisco, CA · On-site

$35 - $40/hr

Annotate visual 3D data (LiDAR/Point Cloud) and 2D camera imagery using bounding boxes, cuboids ... ML goals, and new annotation platforms. You will be at the forefront of AI development ...

Annotate visual 3D data (LiDAR/Point Cloud) and 2D camera imagery using bounding boxes, cuboids ... ML goals, and new annotation platforms. You will be at the forefront of AI development ...

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Lidar Annotation information

See salary details

$50.5K

$111.3K

$137.5K

How much do lidar annotation jobs pay per year?

As of Jun 21, 2026, the average yearly pay for lidar annotation in the United States is $111,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $137,000.00 per year, depending on experience, location, and employer.

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

To excel as a Lidar Annotation specialist, you should have keen attention to detail, spatial awareness, and a basic understanding of data labeling or mapping concepts, often supported by a background in GIS, engineering, or related fields. Experience with specialized annotation software such as Labelbox, Scale AI, or Supervisely, as well as familiarity with point cloud data, is commonly required. Strong organizational skills, reliability, and clear communication abilities are highly valued in this role. These skills help ensure the accurate, consistent, and efficient annotation of large datasets, which is critical for applications like autonomous vehicles and mapping solutions.

What does a typical workday look like for someone in a Lidar Annotation role?

A typical workday for a Lidar Annotation professional involves interpreting 3D point cloud data, drawing precise boundaries around objects, and labeling features according to strict project guidelines. You’ll often collaborate with data scientists, machine learning engineers, and project managers to clarify requirements and ensure high-quality outputs. Tasks can range from image segmentation and object classification to verifying the accuracy of other annotators’ work. The role generally offers a blend of independent, focused work with periodic team reviews or feedback sessions, contributing significantly to machine learning model development.

What is a Lidar Annotation job?

A Lidar Annotation job involves labeling and categorizing objects in 3D point cloud data collected by Lidar sensors. This process helps machine learning models recognize objects like cars, pedestrians, and buildings in autonomous driving, robotics, and mapping applications. Annotators use specialized tools to identify and classify data points, ensuring accuracy for AI training. Attention to detail and an understanding of spatial relationships are essential for this role.

More about Lidar Annotation jobs
What are the most commonly searched types of Lidar Annotation jobs? The most popular types of Lidar Annotation jobs are:
What states have the most Lidar Annotation jobs? States with the most job openings for Lidar Annotation jobs include:
Infographic showing various Lidar Annotation job openings in the United States as of June 2026, with employment types broken down into 76% Full Time, and 24% Contract. Highlights an 88% In-person, and 12% Remote job distribution, with an average salary of $111,343 per year, or $53.5 per hour.

Computer Vision AI & ML Engineer

Skild AI

San Mateo, CA • On-site

$127K - $149K/yr

Other

Posted 19 days ago


Job description

Position Overview

We are seeking a Computer Vision AI & ML Engineer to design, build, and deploy advanced perception systems for real-world robotics and automation. You will work across the full machine learning lifecycle-model development, data strategy, evaluation, and production integration-to deliver robust, high-performance vision capabilities. This role combines applied research with hands-on engineering and offers the opportunity to influence both architecture and roadmap decisions.

Responsibilities
  • Develop and optimize deep learning models for depth estimation, object detection, segmentation, tracking, and 3D scene understanding using multi-modal sensor data.
  • Build scalable pipelines for data processing, training, evaluation, and deployment into real-world and real-time systems.
  • Design labeling strategies and tooling for automated annotation, QA workflows, dataset management, augmentation, and versioning.
  • Implement monitoring and reliability frameworks, including uncertainty estimation, failure detection, and automated performance reporting.
  • Conduct proof-of-concept experiments to evaluate new algorithms and perception techniques; translate research insights into practical prototypes.
  • Collaborate with robotics, systems, and simulation teams to integrate perception models into production pipelines and improve end-to-end performance.
Preferred Qualifications
  • Strong experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
  • Background in computer vision tasks such as detection, depth estimation, segmentation, tracking, or 3D scene understanding.
  • Proficiency in Python; familiarity with C++ is a plus.
  • Experience building training pipelines, evaluation frameworks, and ML deployment workflows.
  • Knowledge of 3D geometry, sensor processing, or multi-sensor fusion (RGB-D, LiDAR, stereo).
  • Experience with data annotation tools, dataset management, and augmentation techniques.
  • Familiarity with robotics, simulation environments (Isaac Sim, Gazebo, Blender), or real-time systems.
  • Understanding of uncertainty modeling, reliability engineering, or ML monitoring/MLOps practices.