Machine Learning Engineer – Feed Recommendation Singapore

AppLovin; Singapore; On-site; SGD 80,000 - 120,000; Full time

Benefits offered by this job

High ownership and direct business impact

Startup speed with AppLovin-level scale and resources

Job summary

AppLovin in Singapore is seeking a Machine Learning Engineer to develop large-scale recommendation systems for a next-generation social media platform. The role involves designing scalable pipelines, optimizing models, and collaborating with multiple teams to drive user engagement.

Candidates should have 3–5 years of relevant experience, strong proficiency in Python, and experience with recommendation systems. Join a fast-paced environment where you can shape the future of AI-driven engagement!

Qualifications

• 3–5 years of experience building production-grade ML systems.
• Strong hands-on experience in recommendation systems.
• Proficient in Python and ML frameworks (PyTorch, TensorFlow).
• Experience improving retention or long-term user value is highly valued.

Responsibilities

• Design and deploy scalable recommendation pipelines.
• Develop and optimize CTR/CVR prediction models.
• Collaborate closely with product, engineering, and monetization teams.
• Run offline experiments and online A/B testing to drive measurable gains.

Skills

Building production-grade ML systems

Recommendation systems

Python

ML frameworks (PyTorch, TensorFlow)

Software engineering fundamentals

Large-scale data systems

Job description

About AppLovin

AppLovin makes technologies that help businesses of every size connect to their ideal customers. The company provides end-to-end advertising and AI solutions for businesses to reach, monetize and grow their global audiences.

We are looking for a Machine Learning Engineer with strong experience in large-scale recommendation systems to help build the next-generation social media platform. You will own critical components of our recommendation stack — including recall, ranking, CTR modeling, and multi-objective optimization — with the goal of driving retention, engagement, and long-term ecosystem growth.

A Day in the Life

• Design and deploy scalable recommendation pipelines
• Develop and optimize CTR/CVR prediction models
• Tackle cold-start challenges for new users and new content
• Run offline experiments and online A/B testing to drive measurable gains
• Collaborate closely with product, engineering, and monetization teams
• Continuously iterate on model performance, latency, and system reliability
• Improve user retention through intelligent content recommendation
• Drive measurable lift in engagement and monetization metrics
• Build core ranking mechanics beyond incremental model tuning
• Shape the foundation of a scalable, long-term content ecosystem

Qualifications

• 3–5 years of experience building production‑grade ML systems
• Strong hands‑on experience in recommendation systems
• Experience in one or more:
  • Recall systems / candidate generation
  • Multi-task or multi-objective optimization
• Proficient in Python and ML frameworks (PyTorch, TensorFlow, etc.)
• Strong software engineering fundamentals
• Experience with large‑scale data systems and distributed training is a plus
• Experience improving retention or long-term user value is highly valued

Why Join This Venture

• Build 0‑to‑1 systems inside a proven AI powerhouse
• High ownership and direct business impact
• Startup speed with AppLovin‑level scale and resources
• Opportunity to shape a new growth engine for the company

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 [e-mail].

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.

To support an efficient and fair hiring process, we may use technology‑assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers.