About Coverstar

Coverstar is building the first safe, creative, AI-native social platform for Gen Alpha. We’re building a world where the next generation can create, connect, and grow with technology that’s fun, expressive, and safe by design. Read more on our Careers Page.

We’re backed by top investors like a16z, moving fast, and hiring a mission-aligned AI Engineer to help us power the next generation of personalized content and community.

What You’ll Do

This role offers a rare chance to architect a recommendation engine from the ground up putting you in the driver’s seat as our in-house specialist and technical authority.

As our AI Engineer/Researcher, you’ll:

• Design, build and deploy recommendation engines for the “for you” video feed, livestreams, and other systems
• Design and optimize personalization systems (user embeddings, clustering, collaborative filtering, etc.)
• Work closely with our CTO, AI engineers and PMs to ship live features, not just models
• Shape the early technical foundation of our AI pod (team, tools, experiments)
• Work hands-on with our data lake, the backbone of the system’s training pipeline.

You Might Be a Fit If You:

• Have 3+ years of hands-on ML/AI experience (recommendation and personalization systems)
• Ideally, you’ve contributed to an app widely recognized for its outstanding recommendation engine. (Youtube, Meta, Spotify, Netflix, TikTok )
• Built or contributed to real-time recommendation systems (e.g., content feeds, match suggestions, etc.)
• Track record of creating production-ready AI-Pipelines.
• Know your way around collaborative filtering, content-based filtering, RNNs, Hybrid recommender approaches.
• Experience of using Transformers (Generative recommenders/session based recommenders), Reinforcement Learning based recommender engines and **Federated Recommender System(FRS)**s is huge advantage