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.
- 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 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
- 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 pre-IPO equity. Our comp range reflects the full scale of expected compensation for this role. Offers are calibrated based on experience, skills, impact, and geographies. Most new hires land in the lower half of the band, with the opportunity to advance toward the upper end over time.
- 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
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.
Top Skills
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
