Machine Learning Platform Engineer

About this role

PrizePicks is seeking a Machine Learning Platform Engineer to design and operate scalable ML infrastructure that powers real-time decision-making across their sports betting platform. You'll bridge data science experimentation and production by building low-latency inference services, feature stores, and MLOps pipelines that handle millions of daily transactions.

What you'll do

• Design and build end-to-end ML infrastructure to transition experimental models into production-grade services
• Develop low-latency inference deployment systems serving model predictions in milliseconds for oddsmaking and risk analysis
• Create and optimize a centralized feature store supporting model training across multiple business domains
• Implement MLOps workflows including automated retraining, monitoring, and CI/CD with focus on data drift detection
• Collaborate with Infrastructure team on ML platform components and establish best practices for model deployment
• Own ML systems end-to-end in production including on-call support and incident response

What they're looking for

• Python (expert level)
• Streaming architectures (Kafka, Flink, Google PubSub)
• MLOps tools (SageMaker, VertexAI, Vector DBs, Graph Databases)
• Docker and Kubernetes containerization
• Low-latency system design (<100ms inference)
• Caching systems (Redis, Elasticsearch)
• Go, C++, or Rust (for high-performance layers)
• Real-time data processing and monitoring