Machine Learning Engineer Intern at AppLovin

A Day in the Life 

At AppLovin, we’re at the forefront of the advertising technology industry. Our cutting-edge platform connects businesses with their potential customers using advanced machine learning technologies. With state-of-the-art ML infrastructure and models, our system rivals those of industry giants. We take pride in providing top-of-the-line compensation packages in the industry and are actively seeking extraordinary machine learning engineers to join our exceptional team.

We are in search of a Machine Learning Engineer Intern to become a member of our impactful Research Science team. In this role, you will play a pivotal part in developing cutting-edge deep learning architectures and advancing our ML infrastructure. If you’re looking for a learning opportunity that will allow you to push the boundaries of machine learning technology, build multi-billion dollar businesses with advanced algorithms, and work in a dynamic, innovative environment, this is the opportunity you’ve been waiting for. This will be a 2-3 month long internship and could start in both Spring and Summer 2024 (depending on graduation date).

Requirements

• You are currently working towards earning a Ph.D. in Computer Science or a related quantitative / engineering field
• Knowledge in deep learning architectures and frameworks (e.g., PyTorch, TensorFlow).
• Solid programming skills in Python and proficiency in relevant ML libraries.
• Excellent problem-solving abilities.
• Strong communication skills and the ability to work collaboratively in a team environment

Preferred Qualifications

• Experience in Recommendation System Research: Candidates with a background in developing or researching recommendation algorithms or systems.
• Achievements in CS or Math Competitions: We value candidates who have received awards or recognition in computer science or mathematics competitions.
• Non-Academic Technical Experience: Participation in events like hackathons is highly regarded, demonstrating practical and innovative technical skills outside of formal education.