We’re the fastest-growing sports gaming company ever.
We build innovative games and products for American sports fans.
Founded in 2020, our team built four of today’s most widely played fantasy games and recently launched our Underdog Sportsbook. We are the only sportsbook to ever launch on our own home grown technology, which allows us to build different and innovative experiences. We believe there’s so much more to be built for sports fans, and we’ll continue to win by building the best products and experiences for our customers.
The opportunity in front of us to become the biggest company in our space is massive; after all, we’re currently sitting in the fastest-growing consumer industry in the U.S. In just over two years, we reached a nearly $500 million valuation through some of the best investors in the game, including Mark Cuban, Kevin Durant, BlackRock, and SV Angel. We are many times larger now and our growth is not slowing down.
At Underdog, we believe that sports are for everyone and are building a tomorrow for every fan. Want to help create that future? Join us.
About the role and why it’s unique:
- As a Machine Learning Engineer on the Data Platform team, you’ll be developing and designing low latency Machine Learning (ML) inference systems to enable real time updates on the UD application
- Build internal tools and services to accelerate UD’s model building and deployment process
- Write low latency application code that are sophisticated and fast for complex, data science infrastructure
- Build frameworks to measure and analyze model performance and accuracy in production environments
- Mentor junior engineers, 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 5 years of experience building low latency systems on a cloud environment (e.g. AWS, GCP, Azure)
- Advanced proficiency with C/C++, Rust, or Go
- Familiarity with SQL
- Strong proficiency with SageMaker, Databricks, and/or comparable ML platforms
- Highly focused on delivering results for internal and external stakeholders in a fast-paced, entrepreneurial environment
- In depth knowledge of statistical concepts such as univariate and bivariate distributions, regression models, and binomial models
- Experience with data streaming frameworks such as Apache Kafka, Apache Flink, or Kinesis
- Familiarity with containerization and orchestration technologies such as Docker, Kubernetes, or ECS
- Excellent leadership and communication skills with ability to influence and collaborate with stakeholders
Even better if you have:
- Strong interest in sports
- Prior experience in the sports betting industry
- Experience in building low latency systems or ML inference systems
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.
What we can offer you:
- 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.
Top Skills
What We Do
Underdog Fantasy is one of the fastest-growing sports companies on the market. Founded by a team of industry veterans, Underdog is bringing fun, approachable contests and games to the masses. We’re looking to innovate an already exciting space and provide the best possible experience to our enthusiastic users.
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