Senior Machine Learning Engineer

About This Role

Join an innovative technology team as a Machine Learning Engineer to analyze complex 3D body scan data and health metrics. This role involves transforming high-dimensional spatial data into actionable insights for personalized health and wellness applications.

Responsibilities

• Develop, train, and deploy machine learning and deep learning models for spatial analysis of 3D human body scans.
• Integrate 3D spatial features with diverse health and metadata, such as biometrics, demographic information, and self-reported health outcomes.
• Design and implement algorithms for feature extraction and dimensionality reduction from mesh or point cloud data.
• Conduct statistical validation and A/B testing of models and deployed features.
• Collaborate with software engineers and domain experts to deploy scalable solutions into production.
• Generate clear and compelling visualizations and reports to communicate complex analytical results to stakeholders.

Requirements

• 3+ years professional experience as Data Scientist or Machine Learning Engineer
• Strong foundation in machine learning, spatial statistics, and deep learning
• Proven ability to take a model from research/prototype to production deployment
• Expert level Python and scientific computing stack (Pandas, NumPy, SciPy, Scikit-learn)
• Deep Learning Frameworks: PyTorch and/or TensorFlow/Keras
• Cloud computing technologies (AWS, Azure, GCP)
• Strong background in statistical modeling, predictive modeling, and experimental design
• Experience with computer vision tasks relevant to 3D geometry (registration, segmentation, shape analysis)
• Familiarity with spatial statistics and techniques for analyzing geometric features

Qualifications

• Bachelor’s or Master’s in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related quantitative field.
• Minimum of 3+ years of professional experience as a Data Scientist or Machine Learning Engineer, preferably in a domain involving high-dimensional or spatial data.

Nice to Have

• Proficiency in Linux
• Experience working with 3D point clouds and/or mesh data structures (e.g., PLY, OBJ, USDZ, STL formats)
• Familiarity with libraries for geometric processing and visualization (Open3D, PCL, Trimesh)
• Knowledge of geometric deep learning techniques (e.g., PointNet, CNN, DGCNN, GCNs/Graph Neural Networks)
• Startup experience
• Docker, Kubernetes
• 3D modeling in Blender

Skills

* Required skills

Benefits