Machine Learning Engineer – Feed Recommendation
AppLovin - Singapore
Posted Mar 9, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
- Not verified last checked Jun 13, 2026
- Salary
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- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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Schedule
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Machine Learning Engineer – Feed Recommendation Singapore 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. 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 . 【The Role】 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 - Improve multi-objective ranking strategies (retention, monetization, diversity, long-term value) - Tackle cold-start challenges for new users and new content - Run offline experiments and online A/B testing to drive measurable
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