Job Application for Research Scientist, Gemini Information Tasks at DeepMind

Snapshot

We are looking for a research scientist who will drive research in Gemini for information tasks. The candidate will primarily work on post-training, but could potentially also work on model-external interventions.

About Us

Our team works on improving Gemini on tasks where users interact with the model to complete information journeys; this includes improving helpfulness and factuality of Gemini models. To this end, we have developed novel post-training innovations to improve the quality, groundedness and factuality of Gemini models in search on mode. Our work impacts product surfaces including AI Mode, Gemini App, AI Studio and Vertex AI.

The Role

In this role, we expect the candidate to work on improving Gemini for information tasks, focusing on quality of information-seeking responses (helpfulness, factuality, grounding, and other aspects). It is an opportunity to explore fundamental issues in modeling and data interventions for information-seeking scenarios, with very significant opportunities in shaping Google’s products in this space.

Key responsibilities:

Research on post-training (e.g., RL and SFT) for information-seeking scenarios in Gemini
Research on novel evaluation methods for improving model quality, grounding and factuality
Research on orchestration of tool calls, and improved retrieval methods, for information-seeking scenarios

About You

I am a director of research in the GenAI unit in GDM. I am one of the GDM leads working on factuality, investigating novel recipes for post training involving retrieval, particularly Google search.

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

PhD in a relevant area, or an equivalent research/publication record
Number of years experience: anything from recent PhD onwards
Strong software-engineering skills in addition to a research background

In addition, the following would be an advantage: (require maximum of 5 and minimum of 3 items)

Experience in reinforcement learning
Experience in post-training methods
Experience in LLMs for information-seeking scenarios

The US base salary range for this full-time position is between $141,000 - $202,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

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Describe your core expertise. What are your main areas of interest?

Describe a specific research or production project where you utilized Reinforcement Learning from Human Feedback (RLHF) or Supervised Fine-Tuning (SFT) to significantly improve the factuality or grounding of a large language model (LLM) for an information-seeking task.

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Research Scientist, Gemini Information Tasks

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