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Freelance Point Cloud Modeling Jobs (NOW HIRING)

... point cloud analysis, object detection, segmentation, and scene understanding. • Train, optimize, and deploy deep learning models using PyTorch, TensorFlow, or equivalent frameworks on cloud ...

Lead CAD Technician / Designer

Bethel, NC · On-site

$25 - $34.25/hr

LiDAR point cloud modeling Knowledge & Experience * Utility and NEC drafting standards * Civil and electrical design principles * Utility construction methods * Survey data interpretation

Lead CAD Technician / Designer

Charlotte, NC · On-site

$24.75 - $34.25/hr

LiDAR point cloud modeling Knowledge & Experience * Utility and NEC drafting standards * Civil and electrical design principles * Utility construction methods * Survey data interpretation

Lead CAD Technician / Designer

Charlotte, NC · On-site

$24.75 - $34.25/hr

LiDAR point cloud modeling Knowledge & Experience * Utility and NEC drafting standards * Civil and electrical design principles * Utility construction methods * Survey data interpretation

Experience working with vector, raster, point-cloud, and sensor datasets. * Excellent analytical ... Build predictive models, time-series forecasting solutions, and causal inference frameworks.

Experience working with vector, raster, point-cloud, and sensor datasets. * Excellent analytical ... Build predictive models, time-series forecasting solutions, and causal inference frameworks.

Experience working with vector, raster, point-cloud, and sensor datasets. * Excellent analytical ... Build predictive models, time-series forecasting solutions, and causal inference frameworks.

Showing results 21-40

Freelance Point Cloud Modeling information

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$14

$47

$132

How much do freelance point cloud modeling jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for freelance point cloud modeling in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What skills and qualifications are needed to thrive as a freelance point cloud modeling specialist?

To thrive as a Freelance Point Cloud Modeling Specialist, you need expertise in 3D modeling, spatial data interpretation, and a solid understanding of surveying or architecture fundamentals. Familiarity with software such as Autodesk ReCap, Bentley Pointools, or CloudCompare, as well as experience handling large datasets, is typically required. Strong problem-solving, attention to detail, and effective client communication are standout soft skills in this field. These competencies ensure the accurate transformation of point cloud data into actionable models, meeting client specifications and supporting high-quality project delivery.

What is the difference between Freelance Point Cloud Modeling vs Freelance 3D Modeling?

AspectFreelance Point Cloud ModelingFreelance 3D Modeling
Skills & CertificationsLiDAR data processing, CAD, 3D scanningPolygon modeling, texturing, rendering
Work EnvironmentField data collection, software for point cloud processingDesign studios, software like Blender, Maya
Industry UsageConstruction, surveying, architectureEntertainment, product design, animation
Search & Comparison IntentFocus on point cloud data, scanning, and modelingFocus on artistic and detailed 3D models

Freelance Point Cloud Modeling specializes in converting LiDAR and scan data into 3D models for technical applications, while Freelance 3D Modeling covers a broader range of artistic and design projects. Both roles require 3D skills but serve different industry needs.

What are common challenges faced by freelance point cloud modelers when working with clients remotely?

Freelance point cloud modelers often encounter challenges related to data transfer and communication when collaborating with clients remotely. Large point cloud files can be difficult to share efficiently, requiring the use of secure cloud storage or specialized file transfer services. Additionally, aligning expectations regarding project scope, accuracy, and deliverables is crucial, as misunderstandings can arise without clear communication. Building effective workflows for feedback and revisions helps ensure smooth collaboration and client satisfaction.

What is freelance point cloud modeling?

Freelance point cloud modeling involves creating 3D models from point cloud data, which are collections of data points in space typically generated by 3D scanners or LiDAR devices. Freelancers in this field use specialized software to process, clean, and convert these data points into accurate digital representations of real-world objects or environments. These models are commonly used in industries such as construction, architecture, engineering, and surveying for tasks like building renovation, site analysis, and digital twin creation. Freelancers offer flexibility and specialized expertise to companies or individuals who need these services on a project basis.
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What cities are hiring for Freelance Point Cloud Modeling jobs? Cities with the most Freelance Point Cloud Modeling job openings:
What are the most commonly searched types of Point Cloud Modeling jobs? The most popular types of Point Cloud Modeling jobs are:
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What job categories do people searching Freelance Point Cloud Modeling jobs look for? The top searched job categories for Freelance Point Cloud Modeling jobs are:
Infographic showing various Freelance Point Cloud Modeling job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 20% Part Time, 1% Temporary, and 4% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.

2.53 3D Machine Learning Engineer

FieldAI

Irvine, CA • On-site

Full-time

Re-posted yesterday


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.