Staff Machine Learning Engineer
April 13
🏢 In-office - Manhattan
Description
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 be asked 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
Requirements
• 5-7+ years of relevant experience developing code in one or more core programming languages (Python, Java, etc.) • 1+ Years of experience in deploying ML models under the constraints of scalability, correctness, and maintainability. • Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, etc.) • 4+ Years of experience designing and building various software architecture. • Deep understanding and knowledge of data structures and software engineering principles • 3+ Years of experience demonstrating technical leadership working with teams, owning projects, defining, and setting technical direction for projects. • Experience with one or more relevant tools (Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis) • Ability to share findings in easy to consume formats, whether that is through dashboards or data modeling. • Conduct regular design process reviews and ensure development standards within the team. • Working with leadership to drive adoption of ML solutions to product engineering teams. • Experience working in a cloud environment such as AWS, GCP, Azure. • Experience with Databricks is a plus, their unity catalog, another plus. • Designing and building data pipelines for production level ML infrastructure. • Motivate junior engineers on best practices and latest industry design patterns.
Benefits
• 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 • Apply your experience and intellect as part of an autonomous team with end-to-end ownership of key components of our data architecture • Serve as a mentor to more junior engineers not only in cultivating craftsmanship but also in achieving operational excellence – system reliability, automation, data quality, and cost-efficiency
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