Research Scientist, Recommendation Systems

Research Scientist, Recommendation Systems

Mountain View, California, US

Our team operates at the frontier of modern recommender systems. With a proven track record of innovating and deploying novel deep learning algorithms and systems at scale, we are currently focused on building the next-gen Large Recommendation Models by bridging the gap between LLMs and complex behavioral signals. Our research explores user & item tokenizations, continued pre‑training, and advanced fine‑tuning techniques to build recommendation‑native foundation models.

Our mission is to transform the landscape of recommendation systems using the most advanced AI technologies, delivering massive impact across Google’s flagship products.

As a Research Scientist, you will have the opportunity to build new paradigms using Large Language Models, harnessing the advanced content understanding, long‑context, and reasoning capabilities. You will play a pivotal role in exploring how to integrate data from recommendation domains into foundation models, enabling new capabilities through data curation, Supervised Fine‑Tuning (SFT), Reinforcement Learning (RL) training, and more.

Key responsibilities:

• Research and develop key technologies such as Semantic IDs, generative retrieval/ranking, large user models.
• Build prototypes to demonstrate the "art of the possible" for recommendation systems using the newest AI advances.
• Work closely with product teams to translate research breakthroughs into deployed solutions for flagship products, tackling real‑world challenges at an industrial scale through new recipes.

We are seeking a Research Scientist who can drive new research ideas from conception and experimentation through to productionisation. In this rapidly shifting landscape, we regularly invent novel solutions to open‑ended problems. You should be flexible, adaptable, and comfortable pivoting when ideas don’t work out.

In order to set you up for success as a at Google Deep Mind, we look for the following skills and experience:

• PhD in Machine Learning, Computer Science, or a relevant field (or equivalent practical research experience).
• A proven track record of research excellence (e.g., publications at top‑tier venues like NeurIPS, ICML, ICLR, or significant industry contributions), ranging from recent graduates to experienced researchers.
• Strong software engineering skills to complement your research background.

In addition, the following would be an advantage:

• Proven track record of building recommender / search systems and/or successfully deploying novel deep learning algorithms at industrial scale.
• Skilled in LLM post‑training algorithms and infra, with proficiency in JAX.
• Strong communication skills with a demonstrated ability to drive cross‑functional projects and collaborate effectively across organizational boundaries.

What We Offer

At Google Deep Mind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options. We strive to continually improve our working environment, and provide you with excellent facilities such as healthy food, an on‑site gym, faith rooms, terraces etc.

We are also open to relocating candidates to Mountain View and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility).

U.S. Standard Demographic Questions

Google Deep Mind is subject to certain governmental record‑keeping and reporting requirements for the administration of civil rights laws and regulations. In order to comply with these laws and achieve our goal of a diverse and inclusive workforce, Google Deep Mind invites employees to voluntarily self‑identify their race or ethnicity. Submission of this information is voluntary and refusal to provide it will not subject you to any adverse treatment.

The information obtained will be kept confidential and may only be used in accordance with the provisions of applicable laws, executive…