Machine Learning Engineer

About This Role

This Machine Learning Engineer will join an innovative technology team to develop and deploy ML/DL models for spatial analysis of 3D human body scans, integrating spatial features with health and metadata to derive 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
• 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 our production environment
• Generate clear and compelling visualizations and reports to communicate complex analytical results

Requirements

• 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
• Proven ability to take a model from research/prototype to production deployment
• Deep expertise in Python and its scientific computing stack
• Expertise in cloud computing technologies such as AWS, Azure, GCP
• Deep learning frameworks (PyTorch and/or TensorFlow/Keras)
• Data manipulation (Pandas, NumPy)
• Scientific computing (SciPy, Scikit-learn)
• Strong background in statistical modeling, predictive modeling, and experimental design
• Experience with computer vision tasks relevant to 3D geometry
• 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
• 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

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

Skills

* Required skills

Benefits