About 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