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About the Role
As a Research Scientist at Google, you will conduct research on multimodal LLM and agentic workflows for generative media. You will collaborate with visual generation researchers, focusing on the language and reasoning aspects of multimodal generation and multi-turn editing. Your work will involve designing and post-training models that interpret user intent, ground generation using search and tools, evaluate output quality, and generalize across languages. Google Research builds next-generation intelligent systems for all Google products, utilizing cutting-edge computer science techniques and collaborating across teams to meet business needs.
Responsibilities
- Conduct fundamental and applied research on multimodal LLMs and agentic workflows for generative media, including multi-turn reasoning, planning, instruction following, and tool use.
- Design, prototype, and run experiments on post-training and alignment methods (such as fine-tuning, reinforcement learning, and synthetic data curation) to improve model quality, faithfulness, and controllability.
- Define data pipelines, benchmarks, reward models, and evaluation metrics for multimodal generation and interactive editing under minimal guidance, refining hypotheses through empirical analysis.
- Identify and investigate research opportunities in multilingual, cross-lingual, and cross-script multimodal modeling, collaborating with internal teams to shape research strategy and expand impact.
- Author research papers to share findings in the research community, and partner with Engineering teams to transfer promising research into Google products.
Requirements
- PhD in Computer Science, a related field, or equivalent practical experience.
- Experience with research projects in Large Language Models (LLMs), Natural Language Processing (NLP), or Multimodal Machine Learning.
- One or more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
- 2 years of coding experience.
- 1 year of experience owning and initiating research agendas.
- Research experience or publications in LLM agents (planning, reasoning, tool use, retrieval-augmented generation), multimodal vision-language models, multilingual NLP, or post-training and alignment (fine-tuning, reinforcement learning, reward modeling).
Skills
- Large Language Models (LLMs)
- Natural Language Processing (NLP)
- Multimodal Machine Learning
- LLM agents
- Multimodal vision-language models
- Multilingual NLP
- Post-training and alignment
- Fine-tuning
- Reinforcement learning
- Reward modeling
- Coding
Education Level
- PhD in Computer Science, a related field, or equivalent practical experience.
About the Company
- Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals.
- Google Research is building the next generation of intelligent systems for all Google products.
- Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.