Staff Machine Learning Engineer

FanDuel • Atlanta, GA

5h • Hybrid

About The Position

At FanDuel, data is the heartbeat of our organization. As a Staff Machine Learning Engineer, 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.

Requirements

• 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

Nice To Haves

• 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 + personalization 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.)

Responsibilities

• 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

Benefits

• Amazing benefits above and beyond the basics
• 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
• Generous paid time off (PTO & sick leave)
• Annual bonus opportunities (based on performance)
• Long-term incentive opportunities (based on performance)
• 401k 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, but not limited to, cash bonuses and stock program participation
• Paid personal time off
• 14 paid company holidays
• Paid sick time in accordance with all applicable state and federal laws

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed