Staff Machine Learning Engineer - Search

THE POSITION
Our roster has an opening with your name on it

At FanDuel, data is the heartbeat of our organization. As a Staff Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. You will own critical production ML systems across real-time personalization, delivering billions of recommendations per day, and search, powering high-scale, low-latency discovery experiences for customers across our sportsbook and gaming products. You will tackle complex, still-evolving challenges in ranking, relevance, retrieval, and online decisioning to provide our business with insight and our customers with world-class personalized experiences. Every click our users make, every bet, every touchdown, every fumble, and every play is fair game for us to turn into a stream of knowledge. Your expertise will be used here to make better and faster decisions – outpacing our competition.

Collaboration is at the core of your role. You’ll be the linchpin between engineering teams working downstream to build out our online application and upstream to land necessary data for feature engineering. You’ll also be working with Data Scientists and Analysts to productionize, analyze, and validate AI powered insights. You will be asked to help organize, model, and present our data as a coherent product and offer it to our stakeholders, providing a common information framework that allows FanDuel to intelligently react to what is happening on the field and in the marketplace.

We are looking for Staff Machine Learning Engineer who may be looking to make the move to a big data environment. If this describes you, read on – we want to hear from you!

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

• Designing and implementing intelligent search systems incorporating typeahead search, vector search and ML personalization signals to optimize relevance and user experience, with end-to-end ownership from ideation to production
• Building and scaling multi-layer serving architectures for ML and GenAI/LLM models, making key architectural decisions in ambiguous problem spaces
• Driving the design and evolution of platform capabilities (e.g. CLI, SDK, Infra Automation, Platform Applications) to streamline ML and GenAI/LLM application development and deployment lifecycle across teams
• Contributing to technical strategy and influencing adoption of ML and GenAI/LLM platform solutions across partner engineering teams
• Applying best practices in data security, privacy (e.g. GDPR, CCPA), governance, and data testing frameworks to ensure reliable and compliant data products
• Owning the continuous integration and delivery of production-grade data and ML systems with a focus on scalability, reliability, and cost-efficiency
• An inclusive culture that expects excellence and prioritizes your growth as an engineer and your well-being as a person
• Advance your career within well-defined, skill-based tracks, either as an individual contributor or as a manager – both providing equal opportunities for compensation and advancement
• Operate as part of an autonomous team with end-to-end ownership of key components of our data and ML platform architecture
• Set engineering standards and mentor junior engineers, elevating team practices in system design, reliability, automation, data quality, and operational excellence
  
  

THE STATS
What we're looking for in our next teammate

Required Qualifications

• 7+ years of relevant experience developing code in one or more core programming languages (Python, Java, etc.)
• 4+ years of experience designing and building scalable software architectures, including systems supporting ML, Search or LLM workloads
• 2+ years of experience implementing vector search, semantic search, or embedding-based retrieval systems (RAG workflows) for production ML or AI applications with vector store such as AWS OpenSearch, Elasticsearch, etc
• 2+ years of experience building platform components and frameworks improving ML/AI development and deployment efficiency
• 1+ years of experience driving technical direction, making architectu