Machine Learning Engineer Intern

Match Group • Palo Alto, CA

1d • Hybrid

About The Position

The Tinder ML team applies machine learning across core product domains, including Recommendations, Trust & Safety, Profile, Chat, Growth, and Revenue. Its mission is to enhance user experiences, foster trust, and accelerate business growth. As an intern, you will collaborate with senior engineers to build and deploy ML solutions that advance Tinder’s business goals and gain experience addressing large-scale challenges with cutting-edge technology. The internship program runs from June 1 through August 31, 2027. This is a hybrid role requiring in-office collaboration three days per week in Palo Alto, California.

Requirements

• Practical knowledge of building efficient end-to-end machine learning workflows.
• Proficiency in Python.
• Hands-on experience designing and building machine learning models.
• Foundational knowledge of computer science principles, including data structures and algorithms.
• Currently pursuing a BS/BA or MS in Computer Science or a related field.

Nice To Haves

• Publications in leading machine learning or data science conferences, such as NeurIPS, ICML, RecSys, or KDD.
• Experience deploying machine learning 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 such as Go, Java, or Scala.

Responsibilities

• Design and implement machine learning algorithms for an assigned domain: Recommendation, Trust, Profile, Chat, Growth, or Revenue.
• Gain experience formulating machine learning models for production problems under guidance.
• Work with senior engineers to develop machine learning solutions that further Tinder’s business goals.
• Participate in the annual Tindership Hackathon and present with the team to Tinder employees and a panel of executives.
• Work on challenges aimed at improving the user experience.

What This Job Offers

• Career Level: Intern