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Hardware • Information Technology • Software
Support data preparation, labeling, training workflows, and validation processes for machine learning systems. Execute and monitor ML pipelines, organize datasets, and evaluate model performance.
Top Skills:
C#Python
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The intern will prototype a generative simulator for diverse driving scenarios, evaluate existing tools, and integrate outputs into data pipelines for autonomous driving applications.
Top Skills:
PythonPyTorch
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As a Machine Learning Engineer Intern, you'll modify models for ego-vehicle predictions, optimize loss functions, and evaluate trajectory diversity and accuracy.
Top Skills:
Deep LearningJaxMachine LearningPyTorch
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.
Our Values
Take the Lead
We don't ghost our work or each other. Just as users don't leave their matches hanging, we don't let each other down.
Move Fast
We have a bias for action and urgency. Something that could be done tomorrow would be better if done today.
Better Together
We keep connection at the heart of dating and at the heart of how we work. Just as our users are better when they connect with others, so are we when we collaborate.
Real Talk
We say the hard thing the human way. Just as we ask our users to behave with kindness and candor in our community, we expect Team Tinder to do the same.
Safety First
We act with integrity, transparency, and consistency so people feel safe—whether they're swiping, matching, or working alongside us.
Spark Fun
We have fun to unlock creativity, fuel innovation, and help us build better experiences for daters.
Program Duration
The internship program will run from June 1 through August 28, 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.
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.
#Tinder
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
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
