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Lidar Annotation Jobs in California (NOW HIRING)

Teleo

Lead Perception Engineer

Palo Alto, CA · On-site

$120K - $158K/yr

Develop auto-annotation and auto-labeling tools using SoTA methods, such as VLMs * Define ... Multi-modal data (camera, LiDAR, radar) Nice to Have * Dataset management & slicing * Experience ...

Teleo

Lead Perception Engineer

Palo Alto, CA · On-site

$120K - $158K/yr

Develop auto-annotation and auto-labeling tools using SoTA methods, such as VLMs * Define ... Multi-modal data (camera, LiDAR, radar) Nice to Have * Dataset management & slicing * Experience ...

Rivian

Senior Staff Tech Lead, VLM

Palo Alto, CA · On-site

$265K - $331K/yr

Experience extending foundational models to extra modalities (e.g., LiDAR, Radar, IMU, ego-motion ... annotation vendors. System engineering: Strong proficiency in Python alongside a solid ...

Rivian

Senior VLM Research Lead, Autonomy

Palo Alto, CA · On-site

$265K - $331K/yr

... annotation vendors. * Iterate and optimize performance: Establish rigorous evaluation and ... Experience extending foundational models to extra modalities (e.g., LiDAR, Radar, IMU, ego-motion)

Civil Maps

Senior Technical Recruiter

Berkeley, CA · On-site

Civil Maps' artificial intelligence software aggregates raw 3D data from LiDAR (high-resolution ... annotation in current use. As a result, the company can quickly generate and maintain maps that ...

Civil Maps

Senior Technical Recruiter

Berkeley, CA

Civil Maps' artificial intelligence software aggregates raw 3D data from LiDAR (high-resolution ... annotation in current use. As a result, the company can quickly generate and maintain maps that ...

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

... LiDAR point clouds, 360 photos, audio, and Building Information Models (BIM). • Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high ...

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All JobsLidar Annotation JobsLidar Annotation Jobs in California

Lidar Annotation information

See California salary details

$49.8K

$109.9K

$135.7K

How much do lidar annotation jobs pay per year?

As of Aug 9, 2026, the average yearly pay for lidar annotation in California is $109,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,300.00 and $135,200.00 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 lidar annotation do?

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?

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.

What are the most commonly searched types of Lidar Annotation jobs in California? The most popular types of Lidar Annotation jobs in California are:
What are popular job titles related to Lidar Annotation jobs in California? For Lidar Annotation jobs in California, the most frequently searched job titles are:
What job categories do people searching Lidar Annotation jobs in California look for? The top searched job categories for Lidar Annotation jobs in California are:
Lidar Annotation jobs near you
Infographic showing various Lidar Annotation job openings in California as of August 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $109,885 per year, or $52.8 per hour.

Staff Perception Engineer - Robotics

Knightscope, Inc.

Sunnyvale, CA

$240K - $275K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 28 days ago

Job description

AboutKnightscope

Knightscope (NASDAQ: KSCP) is a security technology company building the nation's first Autonomous Security Force - autonomous machines, AI-driven software, and elite security professionals operating as one integrated managed service. The Company is on a mission to make the United States of America the safest country in the world. One Team. One Force.

About the Role

In this role, you will own the full perception stack for our autonomous security robot platform, from raw LiDAR, camera, and thermal sensor data through 3D object detection, scene understanding, and persistent entity tracking. You will be a technical lead working across robotics, ML, and systems engineering to ship production-grade perception capabilities that power real-time threat detection, incident correlation, and evidence capture in the field.

Location Requirement: Full-time, on-site at Sunnyvale HQ (No relocation provided)


Key Responsibilities

  • Design, train, and deploy 3D perception models, object detection, segmentation, and multi-object tracking, from multi-modal sensor data (LiDAR, camera, thermal, radar) using state-of-the-art BEV and transformer-based architectures.
  • Own the end-to-end ML pipeline from large-scale data curation and annotation strategy through model training, optimization (TensorRT/CUDA), and real-time onboard deployment on edge compute.
  • Build persistent cross-sensor identity: the same person, vehicle, or license plate maintains a stable track across camera handoffs, patrol legs, and time, feeding entity correlation and incident generation downstream.
  • Design and implement evidence-first capture: pre/post-event clips, full-frame and crop media, and structured detection output that is replay-safe and analyst-ready.
  • Explore and integrate Vision-Language Models (VLMs) to enrich detection outputs with scene narration, anomaly reasoning, and long-tail incident understanding, moving K7 beyond bounding boxes toward analyst-ready scene descriptions.
  • Drive technical decisions on architecture, data strategy, and roadmap; mentor engineers across the team.
  • Design and run rigorous offline and closed-loop evaluations; define metrics for safety-critical perception performance across diverse real-world deployment environments.

Required Qualifications

  • 7+ years of hands-on experience at an OEM, AV company, physical security platform, or robotics tech company shipping perception software to production.
  • Deep expertise in 3D computer vision: LiDAR/camera 3D object detection, point cloud processing, multi-view geometry, and sensor fusion.
  • Strong ML fundamentals, CNNs, Transformers, multi-task architectures, with production deployment experience (TensorRT, ONNX, CUDA optimization).
  • Fluency in C++ (real-time systems) and Python; experience with ROS2 and simulation environments (CARLA, Isaac).
  • Production-first mindset demonstrated ability to take models from research to deployed, real-world systems operating under real operational constraints.

Preferred Qualifications

  • Exposure to vision-language models (VLMs): fine-tuning, prompting, or integrating VLM outputs into a perception pipeline for scene understanding or anomaly narration.
  • Familiarity with Vision-Language-Action (VLA) or end-to-end policy models that map sensor observations directly to robot actions, and interest in applying these to active confirmation and repositioning behaviors.
  • Experience with ALPR, face recognition, or ReID systems in deployed security or automotive contexts.
  • Familiarity with evidence integrity, chain-of-custody media, or tamper-evident capture pipelines.
  • Publications or open-source contributions in 3D CV, embodied AI, or autonomous systems.
  • MS or PhD in Computer Science, Robotics, Electrical Engineering, or related field.

Compensation & Benefits

  • Base Salary:$240,000 to $275,000 (DOE)
  • Equity:Stock options
  • Benefits:Medical, dental, vision, 401(k), paid time off
  • Location Requirement:Full-time, on-site at Sunnyvale HQ

Apply