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 recognizes AppLovin as one of the Best Workplaces in the Bay Area, and the company has been a Certified Great Place to Work for the last four years (2021-2024). Check out the rest of our awards HERE.
At AppLovin, we’re powering the future of product discovery and engagement through cutting-edge machine learning. Recommender systems quietly shape the daily lives of billions of people — deciding what we watch, read, play, and buy. They don’t just influence culture; they drive trillions of dollars in market value across ads, commerce, and streaming, fueling economic growth and job creation worldwide, and the space is still growing at double-digit rates annually.
We’re creating a world-class academic-industrial hybrid research group to advance recommender systems. Unlike academia, your work won’t live only in papers — it will be deployed into real products, used by millions, and validated at scale. This is your chance to push the science forward and see your ideas transform how the world discovers content.
- Drive foundational research to create new recommendation models and paradigms.
- Leverage rich live user data and large-scale compute to validate models rapidly.
- Collaborate closely with engineering and product teams to operationalize research.
- Publish findings and contribute to the broader ML and RecSys community.
- Rich real-time data: access to large-scale, diverse, and dynamic user interactions.
- Massive compute & infrastructure: GPU clusters, feature stores, deployment pipelines.
- Rapid experimentation: immediate feedback through A/B testing and online evaluation.
- Direct impact: see your models shape user experiences and business outcomes.
- Cross-disciplinary collaboration: partner with product, design, and engineering teams.
- Balanced path: combine scientific exploration with practical deployment.
We’re looking for rising researchers with strong academic backgrounds and a desire to have real-world impact.
- PhD (or equivalent research experience) in CS, ML, Statistics, or related field.
- Strong background in deep learning.
- Proven track record of research excellence (publications, awards, impactful projects).
- Proficiency in Python and modern ML frameworks (PyTorch).
- Experience with large-scale data and experimentation.
- Publications in top venues (NeurIPS, ICML, ICLR, KDD, RecSys, SIGIR, WWW).
- Experience with sequential modeling, representation learning, or causal inference.
- Knowledge of online experimentation and evaluation methodologies.
- Industry experience deploying ML in production systems.
- The opportunity to shape the next generation of recommendation science.
- A research culture that combines academic rigor with industrial scale.
- Access to world-class infrastructure and live experimentation loops.
- A collaborative environment that rewards both innovation and execution.
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.
Other Types of Pay: Equity eligible
Health Insurance: Medical, Dental, Vision, Life, Disability
Retirement Benefits: 401(k) Retirement Plan
Paid Time Off: Unlimited Discretionary Time Off
Paid Holidays: 10 paid holidays per year
Paid Sick Leave: 80 hours per year
Method of Application: Apply online
Application Window: The application window is expected to close within 30 days of the posting date.
All questions or concerns about this posting should be directed to [email protected].
Top Skills
AppLovin Palo Alto, California, USA Office
1100 Page Mill Rd, Palo Alto, CA, United States, 94304
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