SeatGeek is a technology innovator on a mission to disrupt the $300 billion ticketing industry. We have the product, vision, and team to make life better for performers, venues, and fans, and build a generational consumer brand in the process. All we’re missing is you.
You will join a group that bridges the gap between research and production-ready ML systems. Your work will directly impact how millions of fans discover and purchase tickets, how we optimize pricing and inventory, how we personalize the SeatGeek experience, and how we prevent fraud across our marketplace. You will design and build ML infrastructure and services that operate at scale, turning complex algorithms into reliable, fast, and maintainable systems that drive business value.
You do not need experience with all of these, but we thought you might be curious. What we care about is your experience, skills, and approach to problem solving. Tools can be learned.
The salary range for this role is $145,000-$200,000 USD. Actual compensation packages within that range are based on a wide array of factors unique to each candidate, including but not limited to skill set, years and depth of experience, certifications, and specific location.
SeatGeek is committed to providing equal employment opportunities to all employees and applicants for employment regardless of race, color, religion, creed, age, national origin or ancestry, ethnicity, sex, sexual orientation, gender identity or expression, disability, military or veteran status, or any other category protected by federal, state, or local law. As an equal opportunities employer, we recognize that diversity is a positive attribute and we welcome the differences and benefits that a diverse culture brings. Come join us!
To review our candidate privacy notice, click here.
Work on cutting-edge sports data and analytics. Join a team that's revolutionizing how we understand sports performance with AI and machine learning.
Salary: $140,000 - $200,000
🤖 This salary estimate is calculated by AI based on the job title, location, company, and market data. Use this as a guide for salary expectations or negotiations. The actual salary may vary based on your experience, qualifications, and company policies.
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