{"id":453117,"url":"https://alion.io/job/fanduel-staff-machine-learning-engineer-search","title":"Staff Machine Learning Engineer - Search","company":{"id":174501,"name":"FanDuel","domain":"fanduel.com","url":"https://alion.io/company/fanduel","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":82,"open_postings":13,"ghost_share":0,"stale_share":0.538,"repost_share":0,"time_to_fill_p50_days":65,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Atlanta, United States","New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":159000,"max":208950,"currency":"USD","period":"year","gross":null,"usd_annual":208950},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenSearch","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Spark","optional":false},{"name":"Terraform","optional":false},{"name":"Amazon SageMaker","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"Databricks","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-04-23T17:31:30Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-10-17T19:43:02Z","board_verified":true,"closed_at":null,"days_open":177,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":176},"description":"THE POSITION\n Our roster has an opening with your name on it\nAt 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.\nCollaboration 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.\nWe 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!\nIn 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.\nTHE GAME PLAN\nEveryone on our team has a part to play\nDesigning 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\nBuilding and scaling multi-layer serving architectures for ML and GenAI/LLM models, making key architectural decisions in ambiguous problem spaces\nDriving 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\nContributing to technical strategy and influencing adoption of ML and GenAI/LLM platform solutions across partner engineering teams\nApplying best practices in data security, privacy (e.g. GDPR, CCPA), governance, and data testing frameworks to ensure reliable and compliant data products\nOwning the continuous integration and delivery of production-grade data and ML systems with a focus on scalability, reliability, and cost-efficiency\nAn inclusive culture that expects excellence and prioritizes your growth as an engineer and your well-being as a person\nAdvance 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\nOperate as part of an autonomous team with end-to-end ownership of key components of our data and ML platform architecture\nSet engineering standards and mentor junior engineers, elevating team practices in system design, reliability, automation, data quality, and operational excellence\nTHE STATS\nWhat we're looking for in our next teammate\nRequired Qualifications\n7+ years of relevant experience developing code in one or more core programming languages (Python, Java, etc.)\n4+ years of experience designing and building scalable software architectures, including systems supporting ML, Search or LLM workloads\n2+ 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\n2+ years of experience building platform components and frameworks improving ML/AI development and deployment efficiency\n1+ years of experience driving technical direction, making architectural trade-offs, and influencing engineering decisions across teams\n1+ years of experience collaborating cross-functionally, working with leadership and influencing and driving partner teams to adopt platform capabilities and best practices\n1+ years of experience conducting design reviews and setting engineering standards within a team\nExperience with data and streaming technologies (e.g., Spark, Flink, Kafka, Airflow, Terraform)\nExperience working in cloud environments such as AWS, GCP, or Azure\nExperience designing and building data pipelines for production ML and GenAI/LLM systems\nStrong understanding of data structures, distributed systems, and software engineering principles\nDemonstrated ability to independently own and deliver complex technical projects end-to-end in ambiguous environments\nAbility to communicate technical concepts and insights effectively through dashboards, data models, or design artifacts\nTrack record of mentoring engineers and elevating team-wide engineering practices and technical quality\nPreferred Qualifications\n1+ years of experience working with typeahead / autocomplete systems and integrating ML signals into query understanding or ranking workflows\n1+ years of experience combining outputs from multiple retrieval systems (e.g., vector search + typeahead + personalization models) to improve relevance\n1+ years of experience deploying ML and GenAI/LLM models under constraints of scalability, correctness, and maintainability in production environmentsHands-on experience with ML frameworks (Scikit-learn, PyTorch, TensorFlow, etc.) and familiarity with LLM frameworks\nHands-on experience with ML and GenAI/LLM platforms (e.g., SageMaker, Bedrock, Databricks, etc.)\n\nABOUT FANDUEL\nFanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America’s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry’s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product. \nIn addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.\nThe company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company’s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.\nFanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).\nPLAYER BENEFITS\nWe treat our team right\nWe offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO & sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here: FanDuel Total Rewards. *Benefits differ across location, role, and level.\nFanDuel is an equal opportunities employer and we believe, as one of our principles states, “We are One Team!”. As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included.\nThe applicable salary range for this position is $159,000 - $208,950 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.\nFanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email .\nIt is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. 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