Senior Machine Learning Platform Engineer

Responsibilities

• Build Scalable 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.
• Real-Time Inference at Scale: Build automation for deploying low-latency services to serve model inferences in milliseconds. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
• Feature Engineering & Data Strategy: You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains.
• What you have:
• 5+ years of experience in Platform Engineering, with a proven track record of deploying and maintaining a scalable ML platform in high-traffic production environments.
• 2+ years of experience owning ML systems end-to-end in production, including on-call and incident response.
• Experience with Real-Time Data , proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve model inference in
• MLOps Expertise , deep experience building a platform for managing the full ML lifecycle (training, deploying, monitoring) using tools like SageMaker, VertexAI, Vector DBs, Graph Databases. Managing and scaling caches like Redis or Elasticsearch.
• Proficient with Containerization, Docker, Kubernetes, and cluster-level management.
• Expert in Python, proficiency in Go. C++, or Rust is a strong plus for building high-performance inference layers.
• What makes you stand out:
• Experience implementing infrastructure while enforcing best practices for the deployment of ML Platform.
• Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading.
• Experience building and scaling "Feature Stores" that successfully bridge batch historical data with real-time event streams.
• Enabling self-service for ML and Data Science teams for model development and deployment.
• Enabling AI agents and AI coding for faster and iterative software development.
• Where you'll live:
• While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates. #LI-Remote
• Working at PrizePicks:
• This application period will remain open for 30 days. We're committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting.
• Date Posted: 4/27/2026
• 1st Extension: 5/27/2026
• Benefits you'll receive:
• In addition to your great compensation package, full-time employees will be eligible for the following perks:
• 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 op

Benefits

Additional Information

At PrizePicks, we are the fastest-growing sports company in North America, as recognized by Inc. 5000. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues, including the NFL, NBA, and Esports titles like League of Legends and Counter-Strike. Our team of over 550 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. Ready to reimagine the DFS industry together? As a Senior ML Platform Engineer, you will contribute to building the ML platform at Prizepicks to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet, Deposit Velocity, and Platform Integrity by integrating robust, low-latency ML models across our sports betting and daily fantasy ecosystems.

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