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Match Group

Machine Learning Engineer Intern

Match Group is hiring a Machine Learning Engineer Intern in Palo Alto, United States. It pays $47/hr and Level rates it ; you can apply on Match Group.

Level's read on this job

  • Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
  • The posting mentions PyTorch, TensorFlow and Keras among its tools and skills.
  • Level classes it as an internship.
  • Match Group has 70 other open roles on Level.
  • Posted in the last few days.

AI in this role

PyTorchTensorFlowKerasDatabricks

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 31, 2027. 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

How we rate this

Machine Learning Engineer Intern at Match Group rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

PyTorchTensorFlowKerasDatabricks

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$197k

Use the typical machine learning engineer figure as a reference when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. What's a project where you used PyTorch hands-on?
  2. Walk me through how you've used TensorFlow in your day-to-day work.
  3. What are the limits of Keras that you've run into, and how did you work around them?
  4. What's a project where you used Databricks hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: PyTorch, TensorFlow, Keras, and Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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