Staff Machine Learning Engineer - Search

This role includes responsibility to help unlock the full potential of 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 sportsbook and gaming products. You will tackle complex challenges in ranking, relevance, retrieval, and online decisioning to provide the business with insight and customers with world-class personalised experiences.

• Design and implement intelligent search systems incorporating typeahead search, vector search and ML personalisation signals to optimise relevance and user experience, with end-to-end ownership from ideation to production
• Build and scale multi-layer serving architectures for ML and GenAI/LLM models, making key architectural decisions in ambiguous problem spaces
• Drive 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
• Contribute to technical strategy and influence adoption of ML and GenAI/LLM platform solutions across partner engineering teams
• Apply best practices in data security, privacy (e.g. GDPR, CCPA), governance, and data testing frameworks to ensure reliable and compliant data products
• Own the continuous integration and delivery of production-grade data and ML systems with a focus on scalability, reliability, and cost-efficiency
• Operate as part of an autonomous team with end-to-end ownership of key components of the 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
• Serve as the linchpin between engineering teams building the online application and upstream teams landing data for feature engineering
• Work with Data Scientists and Analysts to productionize, analyse, and validate AI-powered insights
• Help organise, model, and present data as a coherent product, providing a common information framework for intelligent reaction to on-field and marketplace events

• 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 architectural trade-offs, and influencing engineering decisions across teams
• 1+ years of experience collaborating cross-functionally, working with leadership and influencing and driving partner teams to adopt platform capabilities and best practices
• 1+ years of experience conducting design reviews and setting engineering standards within a team
• Experience with data and streaming technologies (e.g., Spark, Flink, Kafka, Airflow, Terraform)
• Experience working in cloud environments such as AWS, GCP, or Azure
• Experience designing and building data pipelines for production ML and GenAI/LLM systems
• Strong understanding of data structures, distributed systems, and software engineering principles
• Demonstrated ability to independently own and deliver complex technical projects end-to-end in ambiguous environments
• Ability to communicate technical concepts and insights effectively through dashboards, data models, or design artifacts
• Track record of mentoring engineers and elevating team-wide engineering practices and technical quality

• 1+ years of experience working with typeahead / autocomplete systems and integrating ML signals into query understanding or ranking workflows
• 1+ years of experience combining outputs from multiple retrieval systems (e.g., vector search + typeahead + personalisation models) to improve relevance
• 1+ years of experience deploying ML and GenAI/LLM models under constraints of scalability, correctness, and maintainability in production environments
• Hands-on experience with ML frameworks (Scikit-learn, PyTorch, TensorFlow, etc.) and familiarity with LLM frameworks
• Hands-on experience with ML and GenAI/LLM platforms (e.g., SageMaker, Bedrock, Databricks, etc.)

• An array of health plans (some as low as $0 per paycheck) including programs for fertility and family planning, mental health support, and fitness benefits
• Generous paid time off (PTO & sick leave)
• Annual bonus and long-term incentive opportunities (based on performance)
• 401(k) with up to a 5% match
• Commuter benefits
• Pet insurance
• Medical, vision, and dental insurance
• Life insurance
• Disability insurance
• Short-term or long-term incentive compensation, including cash bonuses and stock program participation
• Paid personal time off and 14 paid company holidays
• Paid sick time in accordance with all applicable state and federal laws

FanDuel Group is the premier mobile gaming company in the United States and Canada, consisting of a portfolio of leading brands across mobile wagering including FanDuel Sportsbook, FanDuel Casino, FanDuel Racing, and daily fantasy sports, as well as FanDuel TV and FanDuel TV+; the company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, and global offices in Canada and Scotland, and is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator traded on the New York Stock Exchange (NYSE: FLUT).