ML Engineer: Scalable Recommendation Systems

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

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!