Machine Learning - Computer Vision Engineer - Sports Biomechanics

Position Overview

We are seeking a Machine Learning & Computer Vision Engineer to design and implement advanced models for movement analysis, biomechanics, and sports performance tracking across age groupsfrom children to adults. This role focuses on building scalable, AIdriven solutions that power our sports and fitness learning ecosystem, enabling users to capture, analyze, and improve their physical performance through video, sensor data, and interactive feedback.

You will work at the intersection of computer vision, sports science, and applied machine learning, developing algorithms that transform raw video and motion data into actionable insights for training, assessment, and community engagement.

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.