The fastest-growing sports gaming company, ever. We’re here to make sports more fun. We pair intuitive user experiences with innovative game designs to build the best experience for sports fans in America.
Since 2020, we’ve launched four of today’s most widely played fantasy games, and built the Underdog Sportsbook entirely in-house with our own tech. We move fast, act with urgency, and create experiences you won’t find anywhere else.
With a $1.3 billion valuation and backing from investors like Spark Capital, SV Angel, Mark Cuban, Kevin Durant, Adam Schefter, and more, we’re just getting started.
At Underdog, we play and win as a team. We take chances and are unafraid to attack hard problems. We face challenges with ambition and optimism. We play for the love of the game.
We’re Underdog. And winning as an Underdog is just more fun.
Join us.
- 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
- At least 5 years of experience with model lifecycle (optimization, training and serving) in a cloud environment
- Advanced proficiency with Python and SQL
- Strong proficiency with SageMaker, Vertex AI, Databricks, Kubeflow and/or comparable ML platforms or technologies
- Highly focused on delivering results for the Data Science team in a fast-paced, entrepreneurial environment
- Knowledge of statistical concepts such as univariate and bivariate distributions, regression models, and binomial models
- Experience with data technologies like Airflow, Dagster, Spark, and/or dbt
- Strong interest in sports
- Prior experience in the sports betting industry
Our target starting base salary range for this position is between $150,000 and $190,000, plus target equity. The starting base salary will depend on a number of factors including the candidate’s skills and experience, among other things.
- Unlimited PTO (we're extremely flexible with the exception of the first few weeks before & into the NFL season)
- 16 weeks of fully paid parental leave
- A $500 home office allowance
- 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
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.
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