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About AppLovin AppLovin makes technologies that help businesses of every size connect to their ideal customers. The company provides end-to-end advertising 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. 【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 gains Collaborate closely with product, engineering, and monetization teams Continuously iterate on model performance, latency, and system reliability 【The Impact You’ll Make】 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 【Who You Are】 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 Ranking models CTR prediction 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 jobs@applovin.com 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. Please read our Global Applicant Privacy Notice to learn more about how AppLovin processes your personal information.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.