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