Machine Learning Platform Engineer

🕒 August 4

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 28%

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Logo of PrizePicks

PrizePicks

201 - 500 employees

🎮 Gaming

⚽ Sports

Gaming • Sports

PrizePicks is an innovative platform that offers a dynamic and interactive way to engage in daily fantasy sports and esports. Users can make predictions on player performances across various sports, including NFL, NBA, MLB, CFB, and more, with the opportunity to win up to 1000x their entry fee. PrizePicks operates legally in 43 U. S. states, Washington D. C. , and Canada, providing a wide range of betting options, including Pick 'Em and Pick 'Em Arena, where users compete against each other for cash rewards. The company emphasizes user engagement with features such as recurring promos and the Streak game, which is free to play and allows participants to earn by building daily win streaks. PrizePicks ensures secure transactions and fast payouts, enhancing user experience and satisfaction in the sphere of real money sports betting.

📋 Description

• Build end-to-end machine learning infrastructure and establish a platform for transitioning experimental Data Science models into robust, high-availability production services • Build automation to deploy low-latency services serving model inferences in milliseconds • Power real-time decisions across dynamic oddsmaking, risk analysis, and smart deposit defaults • Lead the creation and optimization of a centralized feature store for training complex models across diverse business domains • Work with the Infrastructure team to build and operate core ML platform components for training and experimentation, focusing on developer experience • Champion best practices for model deployment, monitoring, and CI/CD for ML • Implement automated retraining pipelines and observability to detect and address data drift and model degradation • Contribute to scaling and productionizing PrizePicks' core machine learning capabilities

🎯 Requirements

• 3+ years of experience in Platform Engineering, with a proven track record of deploying and maintaining a scalable ML platform in high-traffic production environments • 1+ years of experience owning ML systems end-to-end in production, including on-call and incident response • Experience with real-time data, streaming architectures (Kafka/Flink/PubSub), and building low-latency services to serve model inference in <100ms • Deep experience building platforms for managing the full ML lifecycle (training, deploying, monitoring) using tools like SageMaker, VertexAI, Vector DBs, and Graph Databases • Experience managing and scaling caches like Redis or Elasticsearch • Proficiency with containerization, Docker, Kubernetes, and cluster-level management • Expert in Python and proficiency in Go • C++ or Rust is a strong plus • Experience implementing infrastructure while enforcing best practices for ML platform deployment (standout) • Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading (standout) • Experience building and scaling feature stores bridging batch historical data with real-time event streams (standout) • Ability to enable self-service for ML and Data Science teams (standout) • Experience enabling AI agents and AI coding for faster, iterative software development (standout) • Must be authorized to work for any employer in the U.S.; employment visa sponsorship is unavailable

🏖️ Benefits

• Company-subsidized medical, dental, & vision plans • 401(k) plan with company match • Annual bonus • Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!) • Generous paid leave programs, including 16-week paid parental leave and disability benefits • Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked • Company-wide in-person events and team outings • Lifestyle enhancement program • Company equipment provided (Windows & Mac options) • Annual performance reviews with opportunities for growth and career development

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