Machine Learning - Computer Vision Engineer - Sports Biomechanics

Position Overview

Machine Learning & Computer Vision Engineer

computer vision, sports science, and applied machine learning

Core Responsibilities

Movement & Biomechanics Analysis

• Develop computer vision pipelines to detect, track, and analyze human movement in sports and fitness contexts.
• Build models for posture recognition, joint angle estimation, gait analysis, and performance metrics.
• Ensure algorithms are robust across diverse age groups, body types, and cultural contexts.

Video & Sensor Integration

• Design systems to process video streams, mobile camera inputs, and wearable sensor data.
• Implement realtime feedback loops for training sessions, drills, and fitness assessments.
• Optimize models for mobile deployment and streaming environments.

Machine Learning & AI Innovation

• Apply deep learning techniques (CNNs, RNNs, transformers) for action recognition and biomechanics classification.
• Experiment with generative AI for visual overlays, automated coaching cues, and personalized training insights.
• Prototype rapidly, test hypotheses, and iterate based on user feedback and performance data.

Scalable Platform Development

• Collaborate with product and engineering teams to integrate ML models into a

  SaaS sports platform

  .
• Ensure scalability, efficiency, and accuracy of algorithms across large user bases.
• Contribute to data pipelines, model deployment, and monitoring frameworks.

Required Experience & Attributes

• 5+ years

  of experience in ML, computer vision, or applied AI engineering.
• Strong proficiency in

  Python, TensorFlow, PyTorch, OpenCV

  , and related ML frameworks.
• Experience with

  pose estimation, action recognition, biomechanics modeling, or sports analytics

  .
• Knowledge of video streaming, mobile optimization, and realtime inference.
• Familiarity with backend integration (Node.js, REST/GraphQL APIs) and cloud deployment (AWS, Azure, GCP).
• Strong problemsolving skills and ability to prototype quickly.
• Excellent communication skills to collaborate with sports scientists, product managers, and designers.

Nice to Have

• Background in sports science, kinesiology, or biomechanics research.
• Experience with wearable sensors (IMUs, GPS, HR monitors) and multimodal data fusion.
• Familiarity with AR/VR, motion capture systems, or 3D reconstruction.
• Prior work in sports tech, fitness apps, or health analytics platforms.

Success Metrics

• Accuracy and robustness of movement/biomechanics models across diverse populations.
• Realtime performance (latency, FPS) of video and sensor analysis pipelines.
• User adoption and engagement with AIpowered training features.
• Contribution to scalable SaaS deployment and monetization strategies.
• Speed of prototyping and iteration cycles using AI tools.