Our Mission
As humans, there are few things more exciting than meeting someone new. At Tinder, we’re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive—and rapidly growing.
We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more.
The Engineering team is responsible for building innovative features and resilient systems that bring people together. We're always experimenting with new features to engage with our members. Although we are a high-scale tech company, the member-to-engineer ratio is very high—making the level of impact each engineer gets to have at Tinder enormous.
Our ML team is responsible for the development of machine learning algorithms and systems for recommendations at Tinder. Recommendation algorithms directly determine potential matches on Tinder and optimize the entire ecosystem to drive critical business metrics. You'll have a unique opportunity to join a company with a global footprint while working on a team that’s small enough for you to feel the impact each day.
Where you'll work:
This is a hybrid role and requires in-office collaboration twice per week. This position is located in Palo Alto, CA.
Our ValuesOne 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.In this role, you will:Apply state-of-the-art machine learning techniques, including deep learning, reinforcement learning, causal inference, and optimization, to enhance our foundational recommendation models.Leverage your expertise to deliver highly personalized and curated recommendations tailored to our users' preferences.Develop algorithms that optimize our complex ecosystem to meet multiple disparate objectives.Design and implement cutting-edge machine learning algorithms using deep learning frameworks and distributed data processing frameworks such as Spark.Work with big data (handling 1.6B+ user swipes per day) to improve the accuracy and relevance of recommendations.Collaborate with other machine learning engineers, backend software engineers, and product managers to integrate ML models into our systems, improving user experience and driving business objectives.You’ll need:PhD or MS in machine learning, computer science, statistics, or another highly quantitative field.Hands-on experience in designing and building large-scale recommendation systems.In-depth knowledge of deep neural networks, particularly in the recommendations domain.Proficiency in deep learning frameworks such as TensorFlow, Keras, etc.Proficiency in Python, Java, Scala, or similar programming languages.At least 5 years of professional experience in relevant fields.Nice to have: Experience with causal inference and reinforcement learning.Experience with solving machine learning problems in multi-sided marketplaces.Experience with big data frameworks such as Spark.Demonstrable experience in designing and implementing large-scale ML systems with low latency serving.A strong record of publications in top conferences such as NeurIPS, ICML, and KDD.A deep understanding of the scientific theory behind machine learning techniques.As a full-time employee, you’ll enjoy:Unlimited PTO (with no waiting period), 10 annual Wellness DaysTime off to volunteer and charitable donations matched up to $15,000 annually Comprehensive health, vision, and dental coverage100% 401(k) employer match up to 10% Employee Stock Purchase Plan (ESPP)100% paid parental leave (including for non-birthing parents), family forming benefits, and Milk Stork, which provides access to breast milk shipping for business travel, surrogacy, and employee relocationInvestment in your development: mentorship through our MentorMatch program, access to 6,000+ online courses through Udemy, and an annual $3,000 stipend for your professional developmentInvestment in your wellness: access to mental health support via Modern Health, BetterHelp, and Insight Timer; paid concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidyFree subscription to Tinder GoldCommitment to Inclusion
At Tinder, we don’t just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don’t meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Learn more here:
https://www.lifeattinder.com/dei
If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please contact employeebenefits@matchgroup.com.
