Machine Learning Engineer, E-commerce Recommendation Foundation - USDS

Responsibilities

The E-commerce Recommendation Foundation team is dedicated to building the next-generation recommendation intelligence. We aim to develop a unified Foundation Model that supports multi-business and multi-scenario recommendation systems, covering the full pipeline from retrieval and ranking to re‑ranking, and driving a comprehensive upgrade in intelligence and generative capability.

We believe the future of recommendation systems goes beyond predicting click‑through rates — it lies in understanding the relationship between people and content, and in generating new connections. The team is exploring an event‑sequence‑driven generative recommendation paradigm, deeply integrating large language models (LLMs), multimodal understanding, reinforcement learning, and system optimization to advance recommendation systems toward general‑purpose intelligent agents.

We value original exploration and encourage both research thinking and engineering excellence. Every team member is empowered to propose hypotheses and validate ideas in an open environment — your code and papers may help define the next paradigm of recommendation systems. We seek individuals with a general intelligence mindset to join us in redefining the future of recommendation.

• Build and optimize cross‑scenario shared Foundation Models to enable unified modeling and efficient inference. Advance the event‑sequence‑driven generative recommendation paradigm, integrating multimodal understanding and generative capabilities.
• Apply LLM technologies across retrieval, ranking, and re‑ranking stages; participate in model training, inference optimization, and system co‑design.
• Explore the integration of LLMs / VLMs with recommendation systems to develop adaptive and evolving intelligent recommenders.
• Research end‑to‑end generative recommendation and system optimization methods that balance efficiency and user experience.

• Solid theoretical foundation in machine learning, deep learning, or information retrieval.
• Proficiency in Python and familiarity with mainstream deep learning frameworks ("e.g., PyTorch").
• Strong passion for intelligent recommendation systems and a self‑driven research mindset.

• Experience in large‑scale recommendation system development or large‑model training, with notable technical achievements in a sub‑area.
• Research experience or publications in LLMs, multimodal learning, reinforcement learning, or generative recommendation.
• Familiarity with pre‑training and post‑training processes for large language models (LLMs) or Foundation Models.

Tik Tok USDS Joint Venture LLC is dedicated to the safety and security of millions of Americans who create, discover, and connect with what they love on the apps we operate. The Joint Venture has been established in compliance with the Executive Order signed by President Trump on September 25, 2025. Our foundation is a comprehensive data privacy and cybersecurity program we operate under defined safeguards to protect national security and secure U.S. user data, apps and the algorithm.

We safeguard the U.S. content ecosystem, holding decision‑making authority for trust and safety policies and moderation. USDS Joint Venture helps ensure Americans can continue to express their creativity, discover new hobbies and interests, and build thriving communities and businesses on a global scale.

On‑site presence across teams allows the company to operate with greater speed, alignment, and agility — especially in areas like real‑time decision‑making, team development, and integrated execution. As such, the company is shifting from a hybrid work model to a fully in‑person schedule up to 5 days a week.

Inspiring creativity is at the core of Tik Tok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.

We strive to do great things with great people. We lead with curiosity, humility, and a desire to…