Our Mission
Launched in 2012, Tinder® revolutionized how people meet, growing from 1 match to one billion matches in just two years. This rapid growth demonstrates its ability to fulfill a fundamental human need: real connection. Today, the app has been downloaded over 630 million times, leading to over 97 billion matches, serving approximately 50 million users per month in 190 countries and 45+ languages - a scale unmatched by any other app in the category. In 2024, Tinder won four Effie Awards for its first-ever global brand campaign, “It Starts with a Swipe”™"
Our Values
One Team, One Dream
We work hand-in-hand, building Tinder for our members. We succeed together when we work collaboratively across functions, teams, and time zones, and think outside the box to achieve our company vision and mission.
Own It
We take accountability and strive to make a positive impact in all aspects of our business, through ownership, innovation, and a commitment to excellence.
Never Stop Learning
We cultivate a culture where it’s safe to take risks. We seek out input, share honest feedback, celebrate our wins, and learn from our mistakes in order to continue improving.
Spark Solutions
We’re problem solvers, focusing on how to best move forward when faced with obstacles. We don’t dwell on the past or on the issues at hand, but instead look at how to stay agile and overcome hurdles to achieve our goals.
Embrace Our Differences
We are intentional about building a workplace that reflects the rich diversity of our members. By leveraging different perspectives and other ways of thinking, we build better experiences for our members and our team.
The Role:
We’re looking for a Product Manager II, Recommendations Platform to help the Recs team test, scale, and launch new models and features more efficiently. In this role, you’ll bridge the gap between the Recs ML and Recs Infrastructure teams, making sure the models and systems the ML team builds are deployed smoothly, run reliably, and can scale as Tinder grows.
You’ll partner with the Recs ML PM and Engineering leads to translate model and experimentation needs into clear infra priorities, sequence work across teams, and make sure stakeholders have visibility into timelines, dependencies, and resourcing.
In parallel, you’ll drive improvements to internal tools that make the Recs organization faster and more effective including experimentation systems, Recs Viewer enhancements, debuggability tools, and better dogfooding experiences.
This role is perfect for someone who loves solving technical coordination problems, improving systems, and enabling teams to move faster through clear structure, process, and communication.
This is a hybrid role and requires in-office collaboration three times per week, in Palo Alto CA.