AI Engineer

We’re building the future of high school sports content at PlayOn Sports — where AI, video, and data come together to tell the story of every game. As an AI Engineer on the Data Driven Content team, you’ll help transform raw data streams into short-form video highlights that engage millions of fans, athletes, and families.
In this role, you’ll design, build, and optimize AI-powered systems that generate real-time video content from live sports data. You’ll work at the intersection of computer vision, machine learning, and streaming pipelines, enabling automated highlight generation, scoreboard overlays, and personalized fan experiences at scale.
The ideal candidate combines hands-on ML engineering expertise with a passion for storytelling through sports. You’re excited by the challenge of working with high-volume video (250k+ games/year), real-time signals (scoring, clock, event metadata), and cutting-edge AI techniques.
The outcomes you’ll deliver
• Automated highlight generation: Deliver accurate, compelling short-form videos within minutes of a live event ending.• Scalable AI pipelines: Build and optimize systems that reliably process thousands of concurrent video streams with high accuracy.• Data-driven fan engagement: Enable personalized, automated content that drives subscriptions, ticketing engagement, and ad revenue. In This Role, You Can Expect To

• Build and deploy ML/AI models for computer vision, event detection, and highlight selection.
• Engineer scalable pipelines that connect live data streams (scoring feeds, video signals, event metadata) to content outputs.
• Collaborate with Data Platform, BI/Analytics, and Product teams to deliver data-ready APIs and fan-facing video features.
• Apply prompt engineering, model fine-tuning, and multi-modal learning techniques to improve highlight accuracy and relevance.
• Monitor and optimize performance for latency, accuracy, and cost efficiency across large-scale workloads.
• Contribute to the design of PlayOn’s AI-first content framework, from research through production deployment.

To Thrive In This Role, You Have

• 4+ years in AI/ML engineering or applied research, with strong Python and ML frameworks (PyTorch, TensorFlow, or similar).
• Experience with computer vision models (object detection, tracking, OCR) and/or video analytics.
• Familiarity with real-time data pipelines (Kafka/Confluent Cloud, Flink SQL, or Spark Streaming).
• Comfort working with large-scale cloud infrastructure (AWS S3, Lambda, GPU instances, Snowflake).
• Strong skills in experimental design, model evaluation, and continuous improvement.
• Bonus: knowledge of sports analytics, prior work with video highlight generation, or personalization/recommendation systems.

How You Play

• Ownership over Participation – You take responsibility for achieving holistic outcomes, prioritize key objectives, and adapt quickly when situations require a different approach. You follow through even against the toughest challenges.

• Team over Stars – You are a bridge builder, establishing processes and relationships with teams outside your own. You rally around common goals, find win-win solutions, compromise when necessary, and help others succeed.

• Growth over Comfort – You are driven by a desire to grow and actively seek opportunities to expand your comfort zone, skills, and confidence. You embrace new challenges with curiosity, accepting discomfort and failure as opportunities to learn.

• Fairness over Popularity – You approach decisions with a scientist’s mindset, challenging assumptions and remaining objective. You consider long-term impact over short-term gains, proactively seek others’ perspectives, and manage emotions in decision-making.