Machine Learning Platform Engineer
PrizePicks is seeking a Machine Learning Platform Engineer to contribute to building the ML platform at PrizePicks to scale and productionize its core machine learning capabilities. The role will directly impact key metrics like Time-to-Bet, Deposit Velocity, and Platform Integrity by integrating robust, low-latency ML models across its sports betting and daily fantasy ecosystems.
The engineer will design and build the end-to-end machine learning infrastructure, setting up a platform for transitioning experimental Data Science models into robust, high-availability production services. This includes building automation for low-latency services that serve model inferences in milliseconds, powering real-time decisions across the platform, and leading the creation and optimisation of a centralised feature store required to train complex models across diverse business domains. The role also involves working with the Infrastructure team to build and operate core ML platform components for training and experimentation, championing best practices for model deployment, monitoring, and CI/CD for ML, and implementing automated retraining pipelines and observability for ML systems.
- Design and build the end-to-end machine learning infrastructure, setup platform for transitioning experimental Data Science models into robust, high-availability production services.
- Build automation to deploy low-latency services that serve model inferences in milliseconds.
- Power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
- Lead the creation and optimisation of a centralised feature store required to train complex models across diverse business domains.
- Work with the Infrastructure team to build and operate core ML platform components for training and experimentation, with a focus on developer experience.
- Champion best practices for model deployment, monitoring, and CI/CD for ML.
- Implement automated retraining pipelines and observability for ML systems to ensure data drift and model degradation are caught and addressed instantly.
- 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 (required).
- 1+ years of experience owning ML systems end-to-end in production, including on-call and incident response (required).
- Experience with Real-Time Data, proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve model inference in <100ms (required).
- Deep experience building a platform for managing the full ML lifecycle (training, deploying, monitoring) using tools like SageMaker, VertexAI, Vector DBs, Graph Databases (required).
- Experience managing and scaling caches like Redis or Elasticsearch (required).
- Proficient with Containerization, Docker, Kubernetes, and cluster-level management (required).
- Expert in Python, proficiency in Go (required).
- C++, or Rust is a strong plus for building high-performance inference layers (nice-to-have).
- Experience implementing infrastructure while enforcing best practices for the deployment of ML Platform (nice-to-have).
- Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading (nice-to-have).
- Experience building and scaling "Feature Stores" that successfully bridge batch historical data with real-time event streams (nice-to-have).
- Enabling self-service for ML and Data Science teams for model development and deployment (nice-to-have).
- Enabling AI agents and AI coding for faster and iterative software development (nice-to-have).
- Must be authorised to work for any employer in the U.S. (required).
- Company-subsidised 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.
PrizePicks is a daily fantasy sports operator headquartered in Atlanta, Georgia. Its app lets players predict whether athletes will beat or fall short of projected statistics, and it has added prediction-market contracts regulated by the US Commodity Futures Trading Commission. In January 2026 the lottery and gaming group Allwyn completed the purchase of a 62.3% majority stake, with PrizePicks continuing as a standalone brand.