Machine Learning Engineer, 3D Vision

This is a fully remote position, open to applicants in California, +3 more states.

📋 Description

• Create, train, and implement sophisticated machine learning and deep learning models for intricate spatial analysis of 3D human body scans.

• Transition projects from initial prototyping to production-ready infrastructure.

• Work directly with accurate 3D data to develop high-performance predictive models addressing physiological challenges.

• Integrate 3D spatial features with biometric data, demographic details, and self-reported health outcomes.

• Design and execute algorithms for feature extraction and dimensionality reduction from irregular mesh or point cloud data.

• Perform statistical validation and A/B testing of models and implemented features.

• Collaborate with software developers, clinicians, and biomechanical engineers to embed solutions into production.

• Create visualizations and reports that convey complex analytical outcomes to both technical and non-technical audiences.

• Influence healthcare applications and performance tracking for both adolescent and professional athletes.

⛳️ Requirements

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related quantitative field.

• At least 3 years of professional experience as a Data Scientist or Machine Learning/Computer Vision Engineer, focusing on high-dimensional or spatial data domains.

• Demonstrated ability to independently manage a model from initial research/prototype through to live production deployment.

• Expert-level proficiency in Python and comprehensive knowledge of its scientific computing ecosystem.

• Extensive experience with Pandas and NumPy, as well as SciPy and Scikit-learn.

• High level of proficiency in Linux/Unix-based terminal interfaces and cloud shell environments (AWS, GCP, or Azure CLI).

• Ability to manage computing resources, automate workflows, and troubleshoot cloud infrastructure from the command line.

• Practical experience with PyTorch and/or TensorFlow/Keras in a production setting.

• Strong foundation in statistical modeling, predictive modeling, and experimental design.

• Direct experience with 3D geometry computer vision tasks, including registration, segmentation, and shape analysis.

• Strong understanding of spatial statistics and methodologies for analyzing geometric features.

• Preferred: knowledge of geometric deep learning techniques, such as PointNet, CNN, DGCNN, GCNs/Graph Neural Networks.

• Preferred: hands-on experience with 3D point clouds and/or mesh data structures, including PLY, OBJ, USDZ, and STL.

• Preferred: familiarity with Open3D, PCL, or Trimesh.

• Preferred: experience with scaled deployment using Docker and Kubernetes.

• Preferred: experience with Blender for synthetic data generation or visualization.

🏝️ Benefits

• Generous PTO policy.

• 12 paid US holidays.

• Medical, dental, and vision insurance for you and your family.

• Paid Parental Leave.

• 401k.