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Lidar Annotation Jobs (NOW HIRING)

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 ...

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 ...

Build and maintain annotation software and other internal data tooling. Data Collection ... LIDAR * Robotics (platforms, sensors, or control) * Linux command line * Blender or Unity * Film/TV ...

Build and maintain annotation software and other internal data tooling. Data Collection ... LIDAR * Robotics (platforms, sensors, or control) * Linux command line * Blender or Unity * Film/TV ...

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 ...

Build and maintain annotation software and other internal data tooling. Data Collection ... LIDAR * Robotics (platforms, sensors, or control) * Linux command line * Blender or Unity * Film/TV ...

Build and maintain annotation software and other internal data tooling. Data Collection ... LIDAR * Robotics (platforms, sensors, or control) * Linux command line * Blender or Unity * Film/TV ...

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 ...

Build ingest for video, lidar, and robot trajectories on Ray Data and Daft, with GPU decode (NVDEC ... Annotation & Auto-Labeling: Produce the labels the models need, such as VLM captions, camera pose ...

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 ...

Showing results 41-60

Lidar Annotation information

See salary details

$50.5K

$111.3K

$137.5K

How much do lidar annotation jobs pay per year?

As of Sep 11, 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 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 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 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.

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:

What job categories do people searching Lidar Annotation jobs look for?

The top searched job categories for Lidar Annotation jobs are:

Infographic showing various Lidar Annotation job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 40% Full Time, 55% Part Time, and 4% Contract. Highlights an 39% Physical, 1% Hybrid, and 60% Remote job distribution, with an average salary of $111,343 per year, or $53.5 per hour.

ML Engineer

New York, NY • On-site, Remote

$170K - $185K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 11 days ago


Key responsibilities

  • Build and maintain data pipelines that move data from deployed sensors to annotation, model training, and production deployment.

  • Automate and improve annotation tooling, model performance monitoring, error analysis, and workflows for model management.

  • Contribute to custom Field Engineering implementations by building integrations with scale systems, ERPs, PLCs, and customer-specific reporting.


Job description

Machine Learning Engineer @ Visia
New York, NY (Hybrid/In-person)
About Us
Visia is the first multimodal AI platform custom built for heavy industry. Visia's full-stack physical intelligence platform includes robust sensing systems across imaging modes (cameras, X-rays, cargo X-rays, LiDAR), foundation vision-language models that convert raw sensor data into structured operational intelligence, and software-driven Field Engineering that drives real transformation on-site at some of the world's largest industrial operations.
We deploy our hardware systems powered by our model flywheel across recycling facilities, steel mills, aluminum smelters, ports, and waste-to-energy plants, processing over 1 billion data points a year. When customers adopt Visia they aren't buying a point solution - they are parting with a platform business that turns unstructured optical data into real-time, actionable intelligence for their operations.
What We're Looking For
We're looking for a Platform Engineer to own and accelerate Visia's data flywheel - the engine that makes our fine-tuned models smarter with every deployment. You'll primarily build the tooling and automation that powers our annotation, model training, and data pipelines, ensuring that every image we process makes Solstice better at understanding the physical world.
This is a high-leverage role. The systems you build directly determine how fast we can onboard new customers, new sensor modalities, and new industry verticals. You'll also pitch in on custom Field Engineering implementations when needed and contribute to internal agentic tooling that helps the team move faster.
Responsibilities
  • Data Flywheel & Model Tooling
    • Automate and improve our instance-segmentation and vision-language model annotation tooling, creating smooth, efficient workflows for our annotators and model managers
    • Build and maintain the pipelines that move data from deployed sensors → annotation → model training → production deployment
    • Develop tooling for model performance monitoring, error analysis, and continuous improvement across customer sites
    • Work closely with ML engineers to accelerate the feedback loop between deployed models and training infrastructure
  • Field Engineering Support
    • Contribute to custom Visia implementations for enterprise customers - building integrations with scale systems, ERPs, PLCs, and customer-specific reporting
    • Support Forward Deployed Engineering (FDE) engagements by building reusable tooling and templates that make each deployment faster than the last
    • Help translate customer operational needs into technical specifications and working softwareInternal
  • Tooling & Automation
    • Build agentic tooling to accelerate GTM workflows - automated sales deck generation, customer research, and outreach
    • Collaborate with the CEO on automating operational workflows
    • Contribute to Visia's overall product roadmap and help shape the future of physical intelligence in heavy industry
Who You Are
  • You have strong programming skills in one or more commonly used programming languages (we use Python, TypeScript, and Go)
  • You move fast, ship iteratively, and care about building things that actually work in production
  • You're comfortable working with at least some of the following and eager to learn the rest:
    • Python backend development (Flask, FastAPI)
    • Frontend development (React / React Native)
    • Cloud computing (GCP, AWS, or Azure)
    • CI/CD, IaC, and containerization (Docker, Terraform, GitHub Actions)
    • Databases (SQL, dbt, Postgres, ClickHouse)
  • Bonus: experience with computer vision pipelines, annotation tooling, or ML infrastructure
  • You have proof of your engineering ability through GitHub projects or work experience
What You Might Work On
  • Building automated annotation pipelines that use SAM and vision-language models to pre-label datasets, cutting model iteration cycles by 5-10x
  • Creating model performance dashboards that surface accuracy regressions across customer sites before they become customer issues
  • Integrating Visia with a customer's scale system to automate compliance reporting they currently do by hand
  • Building an internal agent that generates customized sales decks from customer research and Visia's deployment playbooks
Compensation & Benefits
  • Compensation: $140,000-$155,000/yr + ~$30,000/yr in equity ($170,000-$185,000/yr)
  • Health, Vision, Dental + 401(k)
  • Flexible + Unlimited PTO