Research Scientist, Gemini Information Tasks
Skills & Technologies
Requirements
- Experience
- 0+ years
- Education
- PhD
Joblaze summary
The Research Scientist at Google DeepMind focuses on enhancing the Gemini model for information tasks, primarily through post-training techniques and model evaluations. Key skills include a strong foundation in software engineering, reinforcement learning, and experience with large language models. This role is suitable for candidates with a PhD or equivalent research experience, ranging from recent graduates to those with more extensive backgrounds. The position offers a chance to influence significant product developments in AI-driven information retrieval.
Joblaze insights
- Listed about a month ago on Joblaze — tracked directly from Google DeepMind's career page.
- Google DeepMind has 57 other open roles including Research Engineer, Materials Science, Research Scientist: Multilingual, Multicultural and Multimodal LLM, Science & Frontier AI Research - Writer / Communicator.
- 68 active reinforcement learning roles on Joblaze right now.
- 64 active Large Language Models roles on Joblaze right now.
- 2 active Post-training roles on Joblaze right now.
Quick facts
- How much experience is required?
- At least 0 years of relevant experience for this Research Scientist, Gemini Information Tasks role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Large Language Models, reinforcement learning, Post-training.
- What seniority level is this role?
- Google DeepMind targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Scientist, Gemini Information Tasks role at Google DeepMind.
From the original posting
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
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