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Geodesic Jobs in California (NOW HIRING)

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

... 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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

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 ...

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Geodesic information

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$8

$25

$60

How much do geodesic jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for geodesic in California is $25.79, according to ZipRecruiter salary data. Most workers in this role earn between $14.83 and $30.13 per hour, depending on experience, location, and employer.

What is a Geodesic job?

A geodesic job typically relates to geodesy, the science of measuring Earth's shape, gravity field, and spatial positioning. Professionals in this field, such as geodesists or geomatics engineers, use satellite data, GPS, and mathematical models to improve mapping, navigation, and land surveying. Their work is crucial for applications in construction, transportation, environmental monitoring, and space exploration.

What are the key skills and qualifications needed to thrive in the Geodesic position, and why are they important?

To thrive as a Geodesist, you need a strong background in mathematics, physics, and Earth sciences, often backed by a relevant degree such as geodesy, surveying, or civil engineering. Proficiency with geospatial analysis tools, GPS/GNSS technology, remote sensing systems, and industry-standard software like ArcGIS is essential, and certifications in geomatics or surveying can be advantageous. Strong analytical thinking, attention to detail, problem-solving abilities, and effective communication are key soft skills for this role. These competencies and qualities are vital for ensuring accurate measurement and representation of the Earth's surface, which impacts infrastructure, navigation, and scientific research.

What does a typical day look like for a Geodesist and what kinds of projects might they work on?

A Geodesist’s typical day combines both office-based data analysis and fieldwork for gathering precise measurements of the Earth’s features. You may work on projects such as land surveys for infrastructure development, monitoring tectonic plate movements, or calibrating satellite-based positioning systems. Collaboration is common—you’ll often work alongside cartographers, civil engineers, and GIS specialists to interpret and present geospatial information. The variety in day-to-day tasks and project types makes this role dynamic and offers opportunities to contribute to critical scientific and engineering solutions.

What are popular job titles related to Geodesic jobs in California? For Geodesic jobs in California, the most frequently searched job titles are:
What job categories do people searching Geodesic jobs in California look for? The top searched job categories for Geodesic jobs in California are:
Geodesic jobs near you
Infographic showing various Geodesic job openings in California as of July 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 95% Physical, and 5% Remote job distribution, with an average salary of $53,653 per year, or $25.8 per hour.

2.53 3D Machine Learning Engineer

FieldAI

Irvine, CA • On-site

Full-time

Posted 15 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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