via Greenhouse
$135K - 165K a year
Build and maintain machine learning platforms and tools to support model lifecycle and performance analysis in a fast-paced environment.
3+ years experience in ML model lifecycle, advanced Python and SQL skills, experience with big data tools and ML platforms, preferably in sports betting.
At Underdog, we make sports more fun. Our thesis is simple: build the best products and we’ll build the biggest company in the space, because there’s so much more to be built for sports fans. We’re just over five years in, and we’re one of the fastest-growing sports companies ever, most recently valued at $1.3B. And it’s still the early days. We’ve built and scaled multiple games and products across fantasy sports, sports betting, and prediction markets, all united in one seamless, simple, easy to use, intuitive and fun app. Underdog isn’t for everyone. One of our core values is give a sh*t. The people who win here are the ones who care, push, and perform. If that’s you, come join us. Winning as an Underdog is more fun. About the role and why it’s unique: As a Machine Learning Engineer on the Data Engineering team, you’ll partner closely with the Data Science team to build out our foundational Machine Learning platform Build internal tools and services to accelerate UD’s model building and deployment process Build frameworks to measure and analyze model performance and accuracy in production environments Lead technical initiatives, and drive results in a fast-paced, dynamic environment Lead code reviews, provide constructive feedback, and evangelize best practices to maintain code and data quality Keep up to date on emerging ML technologies and trends and focus on iteratively implementing them into Underdog’s engineering systems Who you are: At least 3 years of experience with model lifecycle (optimization, training and serving) in a cloud environment Advanced proficiency with Python and SQL Experience with with big data tools including Spark, Flink, Databricks, Snowflake, S3 Strong proficiency with SageMaker, Vertex AI, Databricks, Kubeflow and/or comparable ML platforms or technologies Experience building recommendation systems Highly focused on delivering results for the Data Science team in a fast-paced, entrepreneurial environment Even better if you have: Strong interest in sports Prior experience in the sports betting industry Our target starting base salary range for this position is between $135,000 and $165,000, plus target equity. The starting base salary will depend on a number of factors including the candidate’s skills and experience, among other things. What we can offer you: Unlimited PTO for full-time employees (we're extremely flexible with the exception of the first few weeks before & into the NFL season) 16 weeks of fully paid parental leave Home office stipend A connected virtual-first culture with a highly engaged distributed workforce 5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents #LI-REMOTE This position may require sports betting licensure based on certain state regulations. Underdog is an equal opportunity employer and doesn't discriminate on the basis of creed, race, sexual orientation, gender, age, disability status, or any other defining characteristic. California Applicants: Review our CPRA Privacy Notice here.
This job posting was last updated on 11/26/2025