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.
Program Duration
The internship program will run from June 1 through August 31, 2026.
Where you’ll work
This is a hybrid role that requires in-office collaboration three days per week in Palo Alto, California.
About the Role
The Tinder ML team drives impact across nearly every core domain of the product — from Recommendations and Trust & Safety to Profile, Chat, Growth, and Revenue. Our mission is to apply machine learning to enhance user experiences, foster trust, and accelerate business growth across Tinder’s ecosystem. With Tinder's global scale and impact, you'll be at the forefront of solving some of the most complex challenges in technology. In this internship program, you will collaborate with senior engineers to build and deploy ML solutions that advance Tinder’s business goals.
What you'll do:
Gain real-world experience on exciting challenges to improve the user experience.
Design and implement machine learning algorithms for the assigned domains: Recommendation, Trust, Profile, Chat, Growth, or Revenue.
Experience the ML model formulation of production problem under the guidance.
Work closely with a Senior Engineers to develop machine learning solutions to further Tinder’s business goals.
Participate in the annual Tindership Hackathon, presenting with your team to the entire Tinder team and panel of executives.
What we're looking for:
Aspiring ML Engineer who’s excited to work on large scale challenges with cutting-edge technology.
Practical knowledge of how to build efficient end-to-end ML workflows.
Proficient in Python.
Hands-on experience in designing and building ML models.
Foundational knowledge of basic Computer Science principles: data structures and algorithms.
Currently pursuing a BS/BA or MS in Computer Science or a related field.
Nice to have:
Publications in top ML or data science conferences (e.g., NeurIPS, ICML, RecSys, KDD).
Experience deploying ML models in production environments.
Familiarity with deep learning frameworks such as PyTorch, TensorFlow, or Keras.
Experience with Databricks, Spark, or Airflow.
Proficiency in additional programming languages like Go, Java or Scala.
The compensation range listed above is representative of the hourly rate offered.
Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in Palo Alto, California. This hourly rate will be subject to a geographic adjustment (according to a specific city, state, and country), if an authorization is granted to work outside of the location listed in this posting.
Commitment 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 speak to your Talent Acquisition Partner directly.
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