FieldAI · 1 day ago
2.53 3D Machine Learning Engineer
FieldAI is transforming how robots interact with the real world by building risk-aware AI systems for various industries. As a 3D Machine Learning Engineer, you will design and maintain advanced machine learning models to process 3D data, collaborating with engineering teams to integrate these models into production environments.
Enterprise SoftwareRobotic Process Automation (RPA)Robotics
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
Qualification
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
FieldAI is pioneering the development of a field-proven, hardware agnostic brain technology that enables many different types of robots to operate autonomously in hazardous, offroad, and potentially harsh industrial settings – all without GPS, maps, or any pre-programmed routes.
H1B Sponsorship
FieldAI has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (9)
Funding
Current Stage
Early StageTotal Funding
$405M2025-08-20Series Unknown· $91M
2025-08-20Series A· $314M
Recent News
Crunchbase News
2025-12-19
2025-10-16
Company data provided by crunchbase