Senior Computer Vision Engineer – Human Pose & Biomechanics
Senior Computer Vision Engineer – Human Pose & Biomechanics Location Remote (Global) Type Full-Time or Contract Company Texas Sports Academy About the Role We are building an AI-powered training app with elite volleyball leadership (including University of Texas coaching staff). The goal An app that watches an athlete perform drills and provides intelligent, biomechanically sound feedback on their form. This is applied AI at a high level — not research for research’s sake. We need a senior engineer who understands • Human pose estimation • Temporal modeling • Video pipelines • Applied deep learning • Biomechanics-driven feature extraction What You’ll Build • Video ingestion pipeline • Pose estimation integration • Joint angle calculation systems • Movement scoring models • Feedback generation engine • Scalable architecture for mobile + backend integration You will be a foundational technical architect of this product. Required Experience • 5+ years in computer vision or applied ML • Strong Python skills • Experience with human pose estimation frameworks (MediaPipe, OpenPose, MoveNet, BlazePose, HRNet, etc.) • Experience processing and analyzing video data • Deep learning experience (PyTorch or TensorFlow) • Experience designing production ML systems You must understand • Joint angle computation • Temporal smoothing • Movement sequence modeling • Feature extraction from keypoints • Real-world model limitations Bonus Points • Athletic or sports background • Experience building mobile ML systems • Experience deploying ML to edge devices • Experience with 3D pose estimation • Startup experience What Success Looks Like Within 90 days • Working squat grading prototype • Clear pose-based feature extraction framework • Reliable joint angle calculations • Movement scoring logic • Architecture roadmap for volleyball drill analysis Take-Home Evaluation You will build a minimal squat grading app Requirements • User uploads squat video • Extract keypoints • Calculate • Knee angle • Hip angle • Depth • Back angle • Output • Score (1–10) • 3 actionable improvement suggestions Deliverables • GitHub repo • README explaining • Model choice • Tradeoffs • Scaling plan • Limitations Time expectation 6–8 hours. Compensation Competitive. Open to global talent. Contract or full-time available. We are not looking for someone who has “experimented” with pose estimation. We are looking for someone who can build a real product. Job Type Full-time Pay $250,000.00 - $300,000.00 per year Work Location Remote Apply tot his job Apply tot his job
