Role overview
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 we're looking for
You will build a minimal squat grading app:
- 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.
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
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Remote Ai Deep Learning Computer Vision