Senior Research Scientist

APPLOVIN (SINGAPORE) PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading tech company in Singapore is seeking a research scientist to enhance user-centric product discovery. The role involves building and optimizing large-scale recommendation systems, analyzing user data, and deploying A/B tests. Candidates should have solid experience in machine learning and deep programming skills in Python. This position will significantly impact user experience and drive business growth.

Qualifications

• Experience with machine learning/deep learning models applied to recommendation issues.
• Strong programming skills in Python along with deep learning framework experience.
• Mathematical background for data interpretation and metrics-based model decisions.

Responsibilities

• Build and optimize large-scale product recommendation systems.
• Process and analyze billions of user interactions for personalization.
• Design and deploy A/B tests to validate models.

Skills

Machine learning

Deep learning

Python

Data interpretation

Product mindset

Tools

PyTorch

Spark

Flink

C++

Java

Job description

At AppLovin, we build systems that connect users with products they love. Our team has a proven track record of driving business impact through technology—developing one of the world's highest-performing recommendation engines that has fueled AppLovin’s ~25x business growth over the past two years. We move fast: here, you can design a new model, launch an A/B test, and ship improvements—all within days or weeks.

We’re looking for research scientists who are eager to solve hard problems in user-centric product discovery and deliver measurable business outcomes from day one.

【A Day in the Life】

• Build and optimize large-scale product recommendation systems that serve relevant, engaging content to millions of users in real-time
• Process and analyze tens of billions of user interactions daily to improve personalization and relevance
• Integrate multimodal signals—tabular, text, image, and video—into a unified recommendation framework
• Design and deploy large-scale A/B tests to validate model performance and drive product strategy
• Collaborate cross-functionally with product, engineering, and data teams to deliver end-to-end recommendation solutions

【Who You Are】

Basic Qualifications:

• Experience applying state-of-the‑art machine learning/deep learning models to real‑world recommendation or ranking problems
• Strong programming skills in Python and hands‑on experience with deep learning frameworks (preferably PyTorch)
• Strong mathematical background with the ability to interpret data and make model decisions based on metrics
• A product‑minded approach with the drive to impact user experience and business growth
• Bonus Qualifications:
• Experience with large‑scale datasets and distributed computing frameworks (e.g., Spark, Flink)
• Proficiency in C++ or Java in addition to Python
• Prior work specifically related to product recommendation, ranking, or personalization systems