Machine Learning Engineer Intern
AppLovin makes technologies that help businesses of every size connect to their ideal customers. The company provides end-to-end software and AI solutions for businesses to reach, monetize and grow their global audiences. For more information about AppLovin, visit: www.applovin.com.
To deliver on this mission, our global team is composed of team members with life experiences, backgrounds, and perspectives that mirror our developers and customers around the world. At AppLovin, we are intentional about the team and culture we are building, seeking candidates who are outstanding in their own right and also demonstrate their support of others.
Fortune recognized AppLovin as one of the Best Workplaces in the Bay Area 2022, and is a Certified Great Place to Work in 2021, 2022 and 2023. Check out the rest of our awards HERE.
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).
- 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
- 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.
AppLovin provides a competitive total compensation package with a pay for performance rewards approach. Total compensation at AppLovin is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Depending on the position offered, equity, and other forms of incentive compensation (as applicable) may be provided as part of a total compensation package, in addition to dental, vision, and other benefits.
US base pay range (total compensation package will be commensurate with experience)
AppLovin is proud to be an equal opportunity employer that is committed to inclusion and diversity. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status, or other legally protected characteristics. Learn more about EEO rights as an applicant here.
If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send us a request at email@example.com.
AppLovin will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in California, learn more here.
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