About the Role
We are looking for a highly skilled Computer Vision Engineer with deep, hands‑on experience in modern video AI. In this role, you will design, build, and deploy production‑grade computer vision systems that power real‑time insights from game film. You’ll work with cutting‑edge models, cloud infrastructure, and emerging AI APIs to push the boundaries of what’s possible in automated video understanding.
This is an opportunity to shape the next generation of sports analytics technology and deliver tools that meaningfully impact coaches, athletes, and programs at every level.
Location
Company location is Atlanta, GA. Hybrid and remote work options are available
Key Responsibilities
- Develop, train, and optimize computer vision models for object detection, tracking, and video understanding
- Build and deploy scalable, production‑ready video AI pipelines on cloud infrastructure
- Integrate modern AI APIs and foundation models (e.g., Gemini, Claude) into existing workflows
- Evaluate emerging AI capabilities and recommend adoption paths as the field evolves
- Collaborate with product and engineering teams to translate requirements into robust technical solutions
- Implement best practices for model performance, reliability, and monitoring in production
- Use AI tools to accelerate development, experimentation, and iteration cycles
- Maintain clear documentation and contribute to internal knowledge sharing
Required Qualifications
- Strong hands‑on experience with modern computer vision frameworks, models, and techniques, including object detection, multi‑object tracking, and video understanding
- Proven experience building and deploying production video AI pipelines on cloud platforms (AWS, GCP, or Azure)
- Familiarity with modern AI APIs and foundation models (such as Gemini or Claude), with the ability to evaluate and integrate new capabilities
- Demonstrated use of AI tools to accelerate development and improve workflow efficiency
- Proficiency with Python and common CV/ML libraries (PyTorch, TensorFlow, OpenCV, etc.)
- Experience with containerization and deployment tools (Docker, Kubernetes, serverless architectures)
- Strong problem‑solving skills and the ability to work in a fast‑moving, collaborative environment
Preferred Qualifications
- Experience with sports analytics, broadcast video, or multi‑camera systems
- Background in real‑time or near‑real‑time video processing
- Familiarity with MLOps practices and model lifecycle management
- Experience optimizing models for performance and cost efficiency in production
- Contributions to open‑source CV/ML projects or published research
What You’ll Bring
- Curiosity and a passion for pushing the boundaries of video AI
- A builder’s mindset — comfortable iterating quickly and delivering high‑quality solutions
- A collaborative approach and strong communication skills
- A desire to work on technology that directly impacts athletes, coaches, and programs
Why Join Us
- You’ll be part of a team that is redefining how video is used in sports evaluation. Your work will directly influence the tools used by coaches and athletes across the country, helping shape the future of recruiting and performance analytics.
- Competitive salary and equity options
