Senior Research Scientist

APPLOVIN (SINGAPORE) PTE. LTD.; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

A leading technology company in Singapore seeks research scientists to enhance product recommendation systems and solve challenging user-centric problems. You will optimize large-scale systems, analyze billions of interactions daily, and work with cross-functional teams to improve user engagement. Strong skills in machine learning and programming, especially in Python, are required. This role is perfect for candidates excited to impact user experience quickly.

Qualifications

• Experience in real-world recommendation or ranking problems is essential.
• Hands-on experience with deep learning frameworks preferred.
• Ability to interpret data and make model decisions based on metrics.

Responsibilities

• Build and optimize large-scale product recommendation systems.
• Process and analyze user interactions to enhance personalization.
• Design and deploy A/B tests to validate model performance.

Skills

Machine learning/deep learning

Programming in Python

Data interpretation

Product-minded approach

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