Senior AI/ML Engineer (Technical Lead)

We are looking for a highly experienced Senior AI/ML Engineer to lead the creation of a next-generation real-time biometric estimation system for global sports broadcasts.

About the Project:
We are building a real-time, non-contact system to estimate athletes’ exertion for live sports broadcasts. Using high-speed video and computer vision, it predicts force metrics with 85%+ accuracy, replacing traditional sensors, with low-latency and robust performance under complex conditions.

Key Responsibilities:

Phase 0 – Pilot

• Design ML architecture for grip estimation
• Train initial model (force sensors + video data)
• Build training & data labeling pipeline
• Validate across diverse athlete profiles
• Achieve 75%+ correlation

Phase 1 – Demo

• Refine model using demo event data
• Implement 2-second per-athlete calibration
• Optimize for edge cases (skin tones, hand sizes)
• Achieve 80%+ correlation

Phase 2 – Production

• Improve accuracy toward 85%+
• Optimize inference to <40ms (P99)
• Implement advanced scoring features

• Production hardening & reliability improvements

   

Required Skills:

• 5+ years of experience in applied machine learning/deep learning
• Strong background in computer vision and image-based regression tasks
• Hands-on experience with PyTorch or TensorFlow for production systems
• Experience with real-time inference optimization (TensorRT, ONNX Runtime)
• Understanding of signal processing and temporal data analysis
• Experience training models on diverse datasets (handling bias, data augmentation)

• Proven track record achieving high-accuracy requirements (>80% on complex tasks)

   

  Strongly Preferred:

• Experience with biomechanical or physiological signal estimation
• Knowledge of optical/visual phenomena (skin blanching, perfusion, micro-tremors)
• Experience with few-shot learning or transfer learning approaches
• Background in sports analytics or human performance monitoring
• Experience with active learning for iterative model improvement

• Published research or patents in computer vision/ML domains

   

  Nice to Have:

• Experience with NIR (near-infrared) imaging or multi-spectral analysis
• Knowledge of pose estimation frameworks (MediaPipe, OpenPose)
• Experience with edge ML deployment on NVIDIA platforms
• Familiarity with time-series forecasting or sensor fusion

Soft Skills:

• Technical leadership: Ability to make critical architectural decisions under uncertainty
• Problem-solving: Creative approaches to novel ML challenges (no precedent for optical grip estimation)
• Communication: Clearly explain complex ML concepts to non-technical stakeholders
• Adaptability: Rapid iteration based on real-world performance feedback
• Ownership: Take full responsibility for model accuracy through systematic experimentation