Responsibilities
- Build and ship human-in-the-loop interfaces that enable internal operators to review, correct, and approve AI-generated sports statistics in real time across thousands of concurrent live streams.
- Design and develop fan-in-the-loop experiences — interactive highlights, live stat overlays, and engagement features — across NFHS Network, GoFan, and MaxPreps.
- Own features end-to-end: from data modeling and API design through frontend implementation and production deployment.
- Integrate AI/ML model outputs (computer vision, LLMs) into production applications, building the service layer between models and users.
- Develop reusable Python service templates and UI component patterns that establish the team’s standard for AI-forward development.
- Collaborate with computer vision engineers, product managers, and data teams to translate pipeline outputs into intuitive, performant user experiences.
- Contribute to system design and architecture decisions within the streaming intelligence program.
- Participate in code reviews, design reviews, and technical documentation.
- Help evaluate and integrate third-party tools and vendor APIs (annotation platforms, model serving infrastructure) as the platform scales.
Requirements
- 3+ years of professional software engineering experience with strong Python skills and a track record of building production web applications and APIs.
- Builder mentality — you’ve shipped end-to-end features from concept to production, not just maintained existing systems. You bias toward action and iterate quickly.
- Experience integrating AI/ML models into user-facing applications (LLM APIs, computer vision pipelines, or similar). You understand the practical challenges of making model outputs useful to real people.
- Solid fundamentals in API design, data modeling, and service architecture. You write clean, testable code and care about the systems you leave behind.
- Familiarity with cloud infrastructure (AWS EKS, S3) and modern data tooling (Snowflake, Kafka, or similar).
- Strong communicator who works well across disciplines — you can talk to a product manager about user flows and a data scientist about model outputs in the same afternoon.
Nice to Have
- Frontend experience with React/TypeScript (especially interactive annotation or dashboard UIs)
- Familiarity with sports data or video analytics
- Experience with annotation tooling (Roboflow, CVAT, Label Studio)
- Interest in developer experience and internal tooling
