Machine Learning Engineer, 3D

About The Company Field AI is a pioneering company dedicated to transforming how robots interact with the real world through advanced embodied AI systems. Our focus is on developing risk-aware, reliable, and field-ready artificial intelligence solutions that address complex challenges in robotics. We leverage innovative approaches that go beyond conventional data-driven or transformer-based architectures, creating robust models that deliver real-world results. Our solutions are already deployed globally across various industries, continuously improving through real-field applications to unlock the full potential of embodied intelligence.

At the forefront of robotic embodied AI, Field AI is revolutionizing industries such as construction, security, mining, and manufacturing. Our autonomous robots operate in diverse and often harsh environments, providing critical insights and automation capabilities. Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, our technology is designed to make a meaningful impact. With a strong commitment to innovation, we aim to set new standards in perception, planning, localization, and manipulation, ensuring our AI systems are safe, explainable, and effective.

Learn more about our work and latest innovations at our website.

About The Role We are seeking a talented 3D Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing, implementing, training, and maintaining state-of-the-art 3D and multimodal machine learning models that process reality capture data such as 3D point clouds, 360-degree photos, and RGBD images. Your contributions will directly impact our capabilities in automated progress tracking, deviation analysis, and semantic scene understanding within construction sites and other operational environments.

You will collaborate closely with software, autonomy, and product teams to ensure seamless integration of AI models into our production systems. The role requires a combination of technical expertise, innovative thinking, and a passion for solving complex perception challenges in robotics. Your work will help advance our autonomous systems’ accuracy, reliability, and efficiency in real-world applications.

Responsibilities

• Design and develop scalable machine learning pipelines for processing large-scale 3D spatial data, including point cloud analysis, object detection, segmentation, and scene understanding.
• Train, optimize, and deploy deep learning models using frameworks such as PyTorch, TensorFlow, or equivalent on cloud platforms like AWS (e.g., SageMaker, EC2).
• Collaborate with software and systems engineers to integrate models into production environments, ensuring high performance and robustness of inference pipelines.
• Analyze and interpret diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360-degree photos, audio, and Building Information Models (BIM).
• Work with labeling and data operations teams to develop effective data annotation strategies, ensuring high model accuracy and generalization across different scenarios.
• Continuously improve model performance through experimentation, hyperparameter tuning, and deployment of updates in live environments.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Robotics, or a related technical field.
• Minimum of 2 years of industry experience developing and deploying machine learning systems for 3D perception, point cloud processing, or spatial understanding tasks.
• Strong expertise in 3D machine learning techniques, including deep learning for point clouds, multi-view fusion, and geometric learning.
• Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or similar.
• Experience with OpenCV, PCL (Point Cloud Library), and other tools for 3D data preprocessing and classical computer vision tasks.
• Hands-on experience with cloud infrastructure (AWS, SageMaker) and containerized workflows for training and deployment.
• Solid understanding of the end-to-end machine learning lifecycle, including experiment tracking, reproducibility, versioning, and optimization for production.
• Ability to work effectively within interdisciplinary teams across software, ML, and product domains.

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.
• Familiarity with MLOps pipelines using Ray, SageMaker, MLflow, or Kubeflow.
• Knowledge of geometric computer vision, robotics, or algorithmic 3D reasoning.
• Exposure to graph neural networks, geodesic computations, or neural implicit representations such as NeRF or Occupancy Networks.
• Deep experience with point cloud and graph learning frameworks like Open3D-ML, Torch-Points3D, PyG, or MMDetection3D.
• Experience developing custom modules for SparseConvNet or 3D transformers.

Benefits

• Competitive salary ranging from $70,000 to $300,000 annually, based on experience and qualifications.
• Opportunities for hybrid or remote work arrangements.
• Comprehensive health, dental, and vision insurance packages.
• Paid time off and flexible work schedules.
• Professional development opportunities, including training and conferences.
• Being part of a cutting-edge team working on impactful robotics solutions across industries.

Equal Opportunity

Field AI is an equal opportunity employer committed to fostering an inclusive environment. We celebrate diversity and are dedicated to creating a workplace where all employees are valued and respected. We do not discriminate based on race, color, gender,