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Google DeepMind
Google DeepMind

Organizing the world's information and making it universally accessible.

Research Scientist, Recommendation Systems

직무데이터 사이언스
경력미들급
위치Mountain View, California, United States
근무오피스 출근
고용정규직
게시2개월 전
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필수 스킬

Machine Learning

About 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 recommendations-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.

The Role

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.

About You

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).

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Google DeepMind 소개

Google DeepMind

DeepMind Technologies Limited, trading as Google DeepMind or simply DeepMind, is a British-American artificial intelligence research laboratory which serves as a subsidiary of Alphabet Inc.

1,001-5,000

직원 수

London

본사 위치

리뷰

10개 리뷰

3.8

10개 리뷰

워라밸

3.8

보상

4.2

문화

3.5

커리어

4.0

경영진

2.8

68%

지인 추천률

장점

Smart and brilliant colleagues

Good compensation and benefits

Work flexibility and remote options

단점

Poor management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and goals

면접 후기

후기 5개

난이도

3.0

/ 5

소요 기간

21-35주

합격률

60%

경험

긍정 60%

보통 40%

부정 0%

면접 과정

1

Application Review

2

Phone Screen/Online Assessment

3

Technical Interview

4

Team Matching Interview

5

Offer

자주 나오는 질문

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Research Experience

System Design