About the Role
The individual will define and drive computer vision strategy, design core algorithms, and deliver scalable solutions that process visual data to extract actionable insights.
Responsibilities
- Lead the architecture and implementation of computer vision pipelines
- Develop models for 2D and 3D pose estimation from multi-view video
- Optimize algorithms for accuracy and computational efficiency
- Collaborate with software and hardware teams to integrate vision systems
- Translate research concepts into production-grade code
- Mentor engineers in best practices for machine learning and computer vision
- Evaluate and select appropriate datasets for training and validation
- Ensure robustness of vision systems across diverse environments
- Work closely with product stakeholders to define requirements
- Troubleshoot and resolve technical issues in deployed systems
- Stay current with advancements in computer vision and deep learning
- Contribute to intellectual property development through patents
- Design experiments to validate model performance
- Implement versioning and testing frameworks for vision models
- Support deployment of systems in real-world operational settings
Compensation
Competitive salary and equity package
Work Arrangement
Hybrid
Team
Team of approximately 5 to 8 engineers organized as a small, high-performing unit
Technology Stack
- Uses Python, C++, PyTorch, OpenCV, and AWS for end-to-end computer vision workflows
- Implements multi-camera synchronization and calibration pipelines
Impact
- Systems directly inform athlete performance and injury prevention strategies
- Technology deployed in professional and collegiate training environments
Available
