We are seeking a visionary, highly skilled, and impact-driven Computer Vision Engineer (3D-focused) to join our Data Science team. This is a role designed for a creative problem solver and technical thought leader—someone who looks at complex, high-dimensional data and translates it into real-world human outcomes.
In this role, you will own the mission of transforming raw 3D body scan data, measurement features, and body composition metrics into actionable insights. Your work will directly impact cutting-edge healthcare applications and optimize performance tracking for both adolescent and professional athletes in the sports/fitness space. If you want to move beyond passive model training and actively pioneer solutions to real-world physical challenges, this is your sandbox.
Note: This position is a contract-to-hire opportunity
Key Responsibilities (Driving Innovation)
Architect & Pioneer: Develop, train, and deploy advanced machine learning and deep learning models for complex spatial analysis of 3D human body scans. You will move fluidly from zero-to-one prototyping to production infrastructure.
Build from Truth: Work directly with ground truth 3D data to creatively build high-performance, robust predictive models that solve tangible physiological pain points.
Cross-Disciplinary Integration: Synthesize 3D spatial features with multi-modal metadata, including biometrics, demographic information, and self-reported health outcomes to reveal comprehensive health insights.
Unlocking Complex Data: Design and implement novel algorithms for feature extraction and dimensionality reduction from irregular mesh or point cloud data.
Scientific Rigor & Validation: Conduct comprehensive statistical validation and A/B testing of models and deployed features to ensure real-world efficacy and safety.
Collaborative Thought Leadership: Act as a technical partner alongside software engineers and domain experts (such as clinicians and biomechanical engineers) to scale and integrate solutions directly into production.
Data Storytelling: Generate clear, compelling visualizations and reports that effectively communicate nuanced, complex analytical results to both technical teams and non-technical stakeholders.
About You
The Problem-Solver Mindset: You are energized by tackling ambiguous, complex technical challenges and excel at manipulating data in all its forms—especially 3D and spatial data.
The Innovator's Foundation: You bring a bulletproof foundation in Python, machine learning, and scientific computing, paired with an insatiable curiosity, creativity, and a proactive, hands-on approach to building solutions.
Real-World Impact Focus: You don't just optimize metrics in a vacuum; you care deeply about how your models perform when applied to a real human body.
Qualifications
Education: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related quantitative field.
Experience: Minimum of 3+ years of professional experience as a Data Scientist or Machine Learning/Computer Vision Engineer, with a focus on high-dimensional or spatial data domains.
Execution: A proven track record of autonomous ownership—taking a model all the way from initial research/prototype to live production deployment.
Programming & Infrastructure
Python Mastery: Expert-level Python and full command of its scientific computing stack.
Data & Math Foundations: Deep proficiency with data manipulation libraries like Pandas and NumPy , alongside scientific computing tools like SciPy and Scikit-learn.
Infrastructure Autonomy: High proficiency in Linux/Unix-based terminal interfaces and cloud shell environments (AWS, GCP, or Azure CLI). You should be fully capable of managing compute resources, automating workflows, and troubleshooting cloud infrastructure directly from the command line.
Machine Learning & Vision
Deep Learning Frameworks: Production experience utilizing PyTorch and/or TensorFlow/Keras.
Statistical Rigor: A strong background in statistical modeling, predictive modeling, and experimental design.
3D Geometry Processing: Direct experience handling computer vision tasks relevant to 3D geometry, such as registration, segmentation, and shape analysis.
Spatial Statistics: Strong familiarity with spatial statistics and specialized techniques for analyzing geometric features.
Preferred Skills (The Toolset of a Thought Leader)
Advanced Geometric Deep Learning: Knowledge of cutting-edge geometric deep learning techniques (e.g., PointNet, CNN, DGCNN, GCNs/Graph Neural Networks) for processing irregular 3D structures.
3D Frameworks: Hands-on experience working with 3D point clouds and/or mesh data structures (e.g., PLY, OBJ, USDZ, STL formats).
Processing Libraries: Familiarity with modern libraries for geometric processing and visualization, such as Open3D, PCL (Point Cloud Library), or Trimesh.
Modern MLOps: Scaled deployment experience using Docker and Kubernetes.
Creative Prototyping: Experience with 3D modeling and asset creation in Blender for synthetic data generation or visualization.
Compensation, Perks & Benefits
Generous PTO policy + 12 paid US holidays
Medical, dental, and vision insurance for you and your family
Paid Parental Leave
401k
Fit:Match is a B2B2C technology company on a mission to revolutionize the apparel industry through data science to deliver increased relevance and satisfaction for shoppers, improve retail economics, and help the industry as a whole make significant strides towards sustainable apparel retail. We are looking for people who share the same passion.
Fit: Match is backed by an investor group including experienced angel investors, institutional firms, and multi-billion dollar retailers. The best part of working at Fit:Match is, without a doubt, the people. We pride ourselves on hiring team members who embody our people characteristics of low ego, collaboration, dependability, and proven domain expertise. At Fit:Match, you would work cross-functionally with another top global talent with experience in the technology, data science, apparel design and fit, marketing, and retail industries. We obsess over growth, speed, and accuracy. We love a scrappy idea, an out-of-the-box growth hack, and live for reimagining and trying new things.
