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3D Machine Learning Jobs in Orange, CA (NOW HIRING)

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D machine learning models for processing reality capture data, contributing to automated progress tracking ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

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 ...

Hadrian Automation

Machine Learning Engineer

Torrance, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Previously worked in aerospace, defense, or manufacturing, and have experience working 3D/CAD/CAM ...

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All Jobs3D Machine Learning Jobs3D Machine Learning Jobs in Orange, CA

3D Machine Learning information

See Orange, CA salary details

$27.2K

$45.5K

$94K

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

As of Aug 23, 2026, the average yearly pay for 3d machine learning in Orange, CA is $45,490.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,700.00 and $49,100.00 per year, depending on experience, location, and employer.

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 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 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.

What are popular job titles related to 3D Machine Learning jobs in Orange, CA?

For 3D Machine Learning jobs in Orange, CA, the most frequently searched job titles are:

What job categories do people searching 3D Machine Learning jobs in Orange, CA look for?

The top searched job categories for 3D Machine Learning jobs in Orange, CA are:

What cities near Orange, CA are hiring for 3D Machine Learning jobs?

Cities near Orange, CA with the most 3D Machine Learning job openings:

3D Machine Learning jobs near you
Infographic showing various 3D Machine Learning job openings in Orange, CA as of June 2026, with employment types broken down into 2% As Needed, 23% Full Time, 68% Part Time, 2% Temporary, 4% Contract, and 1% Nights. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $45,490 per year, or $21.9 per hour.

2.53 3D Machine Learning Engineer

FieldAI

Irvine, CA • On-site

Full-time

Re-posted 12 days ago

Job description

Job Summary:
FieldAI is a company based in Irvine, California, specializing in embodied AI and robotics. They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D machine learning models for processing reality capture data, contributing to automated progress tracking and scene understanding in construction environments.
Responsibilities:
• 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.
Qualifications:
Required:
• 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.
Preferred:
• 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.
Company:
FieldAI is building general robot intelligence for the physical world. Founded in 2023, the company is headquartered in Mission Viejo, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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