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3D Machine Learning Jobs (NOW HIRING)

Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding. * Train ...

Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding. * Train ...

Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding. * Train ...

Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding. * Train ...

Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding. * Train ...

The 3D Simulation group at Zoox is looking for machine learning engineers to bring the latest research in 3D vision to improve diversity and blur the line between simulation and reality. You will ...

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3D Machine Learning information

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$25.5K

$42.6K

$88K

How much do 3d machine learning jobs pay per year?

As of Jun 5, 2026, the average yearly pay for 3d machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a 3D Machine Learning Engineer, and why are they important?

To thrive as a 3D Machine Learning Engineer, you need a solid background in computer science, mathematics, and experience with 3D data processing and machine learning algorithms, typically supported by a relevant degree. Expertise in tools and frameworks like Python, PyTorch or TensorFlow, and libraries such as Open3D or PCL is commonly required, along with familiarity with 3D data formats. Strong problem-solving skills, creativity, and effective communication set top performers apart in this role. These skills enable the development of innovative solutions for complex 3D data challenges, which are crucial for advancements in fields like robotics, computer vision, and AR/VR.

What are some common challenges faced by professionals working in 3D machine learning, and how can they be addressed?

Professionals in 3D machine learning often encounter challenges such as handling large and complex datasets, managing high computational requirements, and ensuring model robustness across diverse 3D data types (e.g., point clouds, meshes, voxel grids). Addressing these challenges typically involves using efficient data preprocessing pipelines, leveraging cloud computing or advanced GPU resources, and staying updated with the latest research on 3D data augmentation and model architectures. Collaboration with multidisciplinary teams—including data engineers, computer vision experts, and domain specialists—is also crucial for overcoming technical obstacles and producing practical, scalable solutions.

What is 3D machine learning?

3D machine learning is a field of artificial intelligence focused on developing algorithms and models that can process and understand three-dimensional data. This includes tasks such as object recognition, scene reconstruction, segmentation, and analysis using 3D data formats like point clouds, meshes, or volumetric grids. Applications of 3D machine learning are found in areas like autonomous driving, robotics, medical imaging, and augmented reality. The field combines techniques from computer vision, deep learning, and geometry processing to interpret complex spatial information.

What is the difference between 3D Machine Learning vs 3D Computer Vision?

Aspect3D Machine Learning3D Computer Vision
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegree in Computer Vision, Computer Science, or related fields; experience with image processing
Work EnvironmentResearch labs, AI development teams, tech companiesImaging labs, robotics, autonomous vehicles, tech firms
Industry UsageDeveloping models for 3D data analysis, sensor data integrationProcessing 3D images, object detection, scene reconstruction

While 3D Machine Learning focuses on creating algorithms that learn from 3D data, 3D Computer Vision emphasizes interpreting and analyzing 3D visual information. Both fields often overlap but serve different primary objectives within AI and imaging applications.

More about 3D Machine Learning jobs
What cities are hiring for 3D Machine Learning jobs? Cities with the most 3D Machine Learning job openings:
What states have the most 3D Machine Learning jobs? States with the most job openings for 3D Machine Learning jobs include:
Infographic showing various 3D Machine Learning job openings in the United States as of May 2026, with employment types broken down into 4% As Needed, 88% Full Time, 4% Part Time, and 4% Temporary. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

3D Machine Learning Engineer

FieldAI

Irvine, CA • On-site

Other

This job post has expired today. Applications are no longer accepted.


Job description

FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.
What You'll Do

  • Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding.
  • Train, optimize, and deploy deep learning models using PyTorch, TensorFlow, or equivalent frameworks on cloud platforms such as AWS (e.g., SageMaker, EC2).
  • Collaborate with software and systems engineers to integrate models into production environments and continuously improve inference pipelines.
  • Analyze diverse sensor inputs, including RGBD imagery, 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 model performance and generalization.
What You Have
  • Bachelor's or Master's degree in Computer Science, Machine Learning, Robotics, or a related technical field.
  • 2+ years of hands-on industry experience developing and deploying machine learning systems for 3D point clouds, perception, or spatial understanding tasks.
  • Strong background in 3D machine learning, with experience in deep learning for point clouds, multi-view fusion, or geometric learning.
  • Strong expertise in Python and deep learning frameworks: PyTorch, TensorFlow, or similar.
  • Familiarity with OpenCV and PCL (Point Cloud Library) for classical computer vision and 3D data preprocessing.
  • Experience training, evaluating, and deploying ML models using cloud infrastructure (e.g., AWS, SageMaker) and containerized workflows.
  • Solid understanding of the end-to-end ML lifecycle, including experiment tracking, reproducibility, model versioning, and optimization for production.
  • Proven ability to work in fast-paced, interdisciplinary teams across software, ML, and product teams.
The Extras That Set You Apart
  • Experience working with BIM data, digital twins, or construction-related sensor data.
  • Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene representations.
  • Familiar with MLOps pipelines using Ray, SageMaker, MLflow, or Kubeflow.
  • Strong foundation in geometric computer vision, robotics, or algorithmic 3D reasoning.
  • Exposure to graph neural networks, geodesic computations, or neural implicit representations (e.g., NeRF, Occupancy Networks).
  • Deep experience with point cloud and graph learning frameworks such as Open3D-ML, Torch-Points3D, PyG, or MMDetection3D.
  • Experience building custom modules for SparseConvNet or 3D transformers.

Our salary range is generous and we consider each individual's background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.
Why Join FieldAI in Irvine?
In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics' hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.
You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.
Be Part of the Next Robotics Revolution
We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.
Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like.
We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected statu
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.