Staff Machine Learning Engineer: Search

PrizePicks is the fastest-growing sports company in North America, recognized for its leading platform in Daily Fantasy Sports. As a Staff Machine Learning Engineer, you will develop and optimize the Global Search architecture to provide a fast and personalized search experience for users, transforming search into a primary gameplay driver.

Responsibilities:

• Architect Global Search: Build the foundational architecture for a unified Global Search entry point that creates a "Single Source of Truth" across Players, Teams, and Game Modes
• Optimize for Speed: Engineer the Prizepicks search stack to achieve <200ms latency targets, evaluating and deciding between Server-side indexing v
• Advanced Retrieval Logic: Implement fuzzy matching, nickname support, and natural language processing (NLP) to handle user queries like "Bron", “lal/LAL/Lakers” or "Rushing Yards" intuitively
• Dataverse Integration: Partner with Data Engineering to ensure the Search Index is fed by real-time streams of projections, live game states, and social data, ensuring results are never stale

Requirements:

• 5+ years of experience in Machine Learning Engineering, with deep expertise in Information Retrieval (IR) and Search technologies
• 3+ years of technical leadership, guiding teams through complex architectural migrations and greenfield builds
• Familiarity with indexing strategies using technologies like Elasticsearch, OpenSearch, Solr, or Vector Databases (Pinecone, Milvus)
• A track record of optimizing API response times and database queries for high-throughput, low-latency applications
• Experience with GCP (Kubernetes, Cloud Functions) and Infrastructure as Code (Terraform)
• Experience building 'Instant Search' or 'Type-ahead' features for high-traffic consumer mobile apps
• Knowledge of mobile-side database technologies (e.g., Realm, SQLite, WatermelonDB) for offline-first or hybrid search architectures
• Experience integrating GenAI or LLMs to power conversational search interfaces