# Research Scientist, Gemini Information Tasks

**Company**: Google DeepMind
**Location**: Mountain View, California, US
**Work arrangement**: onsite
**Experience**: senior
**Job type**: full-time
**Salary**: $147,000 USD - 211,000 + bonus + equity + benefits
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q15733006

**Apply**: https://job-boards.greenhouse.io/deepmind/jobs/7669124?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_c6c0a57f-a27

## Description

We are seeking a research scientist to precisely improve Gemini's information-seeking capabilities. The successful candidate will work on post-training research in Gemini, focusing on quality of information-seeking responses. This role offers an opportunity to explore fundamental issues in modelling and data interventions for information-seeking scenarios, with significant opportunities in shaping Google's products in this space.

**Responsibilities:**

- Conduct research on post-training methods for information-seeking scenarios in Gemini, including reinforcement learning and self-supervised training.

- Develop novel evaluation methods for improving model quality, grounding, and factuality.

- Investigate orchestration of tool calls and improved retrieval methods for information-seeking scenarios.

**Requirements:**

- PhD in a relevant area, or an equivalent research/publication record.

- Strong software-engineering skills in addition to a research background.

**Preferred Qualifications:**

- Experience in reinforcement learning.

- Experience in post-training methods.

- Experience in Large Language Models for information-seeking scenarios.

The US base salary range for this full-time position is between $147,000 USD - 211,000 + bonus + equity + benefits.

## Skills

### Required
- PhD in a relevant area
- Strong software-engineering skills
- Reinforcement learning
- Post-training methods
- Large Language Models

### Nice to have
- Experience in reinforcement learning
- Experience in post-training methods
- Experience in LLMs for information-seeking scenarios

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/deepmind/jobs/7669124?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)