Tech Stack

Description

You will design and implement large-scale recommendation systems for Roblox's discovery surfaces, developing deep learning models for ranking, retrieval, and personalization. Collaborating with researchers and engineers, you will translate cutting-edge research into production systems that impact hundreds of millions of daily active users.

Requirements

• Possessing or pursuing a PhD in computer science, engineering, or related field with thesis aligned to Roblox's research areas.
• Expertise in recommender systems, search, information retrieval, or generative models (e.g., LLMs, VLMs).
• Ability to design systems for efficient personalization using advanced attention mechanisms (e.g., sparse/linear attention).
• Strong research track record with publications in top-tier venues (e.g., SIGIR, KDD, RecSys, ICLR, ICML, NeurIPS).
• Proficiency in Python, C++, Go, or Java with experience building large-scale systems.

Responsibilities

• Design and implement large-scale recommendation systems for discovery across experiences, avatars, and creator content.
• Develop deep learning models for ranking, retrieval, and personalization using multimodal models, LLMs, and generative AI.
• Collaborate with researchers, engineers, and product teams to advance experimentation and accelerate innovation.
• Translate research into production systems impacting hundreds of millions of daily active users.
• Work backward from user and product needs to deliver ML solutions driving engagement and retention.