Research Scientist - Generative AI & LLMs

Google; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google is seeking a Research Scientist to join the Gemini team in Mountain View. You will lead research initiatives on large language models, multi-turn interactions, and evaluation techniques, training and refining foundations for real-world deployments.

You will publish findings and collaborate with internal and external research programs, shaping the direction of core AI capabilities across Google products while meeting deadlines and delivering impactful results.

Qualifications

• PhD in Computer Science, a related field, or equivalent practical experience.
• 2 years of experience leading a research agenda.
• Experience in core ML model development.
• Experience with LLM training and generative models.
• One of more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Responsibilities

• Scope and drive research efforts to improve complex frontier Gemini capabilities, such as multi-turn, factuality and tool-use.
• Review the latest literature to guide research and experimental directions.
• Curate and generate data to evaluate and improve Gemini capabilities.
• Design and implement both human and automated evaluation strategies.
• Design and conduct supervised fine-tuning and reinforcement learning experiments to improve the performance of Gemini capabilities such as multi-turn and factuality.

Skills

2 years of experience leading a res. g

Experience with LLM training and gener

Experience in core ML model develop

2 years of coding experience

1 year of experience leading research

Education

PhD in Computer Science or related field

Publication submissions (CVPR, ICCV, NeurIPS, ICML, ICLR, etc.)

Job description

Google is seeking a Research Scientist to join the Gemini team in Mountain View. You will lead research initiatives on large language models, multi-turn interactions, and evaluation techniques, training and refining foundations for real-world deployments.

You will publish findings and collaborate with internal and external research programs, shaping the direction of core AI capabilities across Google products while meeting deadlines and delivering impactful results.