Staff Machine Learning Engineer

🕒 April 16

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PrizePicks

WebsiteLinkedInAll Job Openings

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

• Architect Scalable ML Systems: Design and build the end-to-end machine learning infrastructure, transitioning experimental Data Science models into robust, high-availability production services. • Real-Time Inference at Scale: Steer the design and deployment of 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: Partner with Data Science to build scalable logging and data pipelines. You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains. • End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD for ML. You will implement automated retraining pipelines and observability tools to ensure data drift and model degradation are caught and addressed instantly.

🎯 Requirements

• 7+ years of experience in Machine Learning Engineering or Backend Engineering, with a proven track record of deploying and maintaining complex ML models in high-traffic production environments. • 3+ years of technical leadership, acting as a lead and driving architecture decisions for consumer applications or scalable backend platforms. • Experience with Real-Time Data: Proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve model inference in <100ms. • MLOps Expertise: Deep experience managing the full ML lifecycle (training, deploying, monitoring) using tools like MLFlow, Kubeflow, Databricks, or SageMaker. • Strong Coding Skills: Expert in Python and SQL; proficiency in Go, C++, or Rust is a strong plus for building high-performance inference layers. • Cloud Native: Deep experience with GCP services (BigQuery, Cloud Functions, GKE, Vertex AI) or AWS equivalents.

🏖️ 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