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3D Lidar Segmentation Jobs (NOW HIRING)

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

... segmentation, and scene understanding. • Train, optimize, and deploy deep learning models using ... imagery, LiDAR point clouds, 360 photos, audio, and Building Information Models (BIM). • Work ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and ... segments. Be Part of the Next Robotics Revolution We are looking for builders who want their work ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and ... segments. Be Part of the Next Robotics Revolution We are looking for builders who want their work ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and ... segments. Be Part of the Next Robotics Revolution We are looking for builders who want their work ...

Tensec

ML Engineer

San Francisco, CA · On-site

$120 - $150/hr

We build models to extract 3D object and line features from dense LiDAR point clouds and imagery ... segmentation, detection, or 3D understanding. * Experience taking a ML model from research ...

Mach9 Robotics Inc

ML Engineer

San Francisco, CA · On-site

$180K - $300K/yr

We build models to extract 3D object and line features from dense LiDAR point clouds and imagery ... segmentation, detection, or 3D understanding. * Experience taking a ML model from research ...

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3D Lidar Segmentation information

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.

What are the key skills and qualifications needed to thrive as a 3D LiDAR segmentation specialist?

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 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.
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Infographic showing various 3D Lidar Segmentation job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 88% Full Time, 8% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Senior Machine Learning Engineer - Perception 3D Segmentation

Zoox

Foster City, CA • On-site

$254K - $350K/yr

Full-time

Medical, Life, PTO

Re-posted 20 days ago

Zoox rating

7.8

Company rating: 7.8 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

213th of 499 rated machine equipment manufacturers

Job description

The Perception team at Zoox is responsible for the robot's understanding of the world, fusing data from Lidar, Radar, and Cameras to create a unified representation of the environment. In this role, you will contribute to the development of our next-generation 3D occupancy and segmentation networks. You will architect and optimize high-performance deep learning models that generate dense, temporally consistent voxel representations of the driving environment. This work is critical for enabling our vehicle to navigate complex urban scenarios, handle rare obstacles, and drive safely in tight spaces by providing precise geometry and motion estimates to downstream planners.
In this role, you will...
  • Design and implement state-of-the-art multi-modal sensor fusion architectures (Lidar, Camera, Radar) to predict 3D occupancy, semantic segmentation, and flow .
  • Develop "vision-first" fusion strategies to enhance geometric understanding and reduce dependency on sparse sensor modalities .
  • Engineer temporal processing modules to improve the stability and consistency of predictions over time.
  • Optimize model architectures for real-time on-vehicle inference, balancing high-fidelity range extension with strict latency constraints .
  • Collaborate with downstream consumers (Tracking, Prediction, Planner) to refine geometric outputs, such as contours and free-space estimations, for complex maneuvering.

Qualifications
  • MS or PhD in Computer Science, Robotics, Machine Learning, or related field with 6+ years of industry experience.
  • Deep expertise in 3D Computer Vision and Deep Learning, specifically with voxel-based or BEV (Bird's Eye View) architectures.
  • Strong proficiency in Python and deep learning frameworks (PyTorch) for model training and design as well as some experience in C++ for model integration.
  • Experience with multi-sensor fusion (Lidar, Camera, Radar) and handling temporal data sequences.
  • Experience with occupancy networks, implicit representations (NeRF/Gaussian Splats), or scene flow estimation.

Bonus Qualifications
  • Experience optimizing models for TensorRT/CUDA to achieve low-latency inference.
  • Familiarity with sparse convolutions or query-based architectures for efficient 3D processing.
  • Experience with Vision Language Model, or multi-modal 3D foundation model, or World Model, or VLA.

$254,000 - $350,000 a year
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

What Zoox employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Zoox

Sourced by ZipRecruiter

Zoox is dedicated to creating the world's first fully autonomous vehicle fleet and the necessary ecosystem to make this technology accessible. Positioned at the crossroads of robotics, machine learning, and design, Zoox strives to deliver the future of mobility-as-a-service in urban settings. We seek exceptional individuals who share our enthusiasm and are eager to join a dynamic and results-driven team.

Industry

Manufacturing

Company size

1,001 - 5,000 Employees

Headquarters location

Foster City, CA, US

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