Senior Research Scientist, Beam

Google•Mountain View, CA

8d•$174,000 - $252,000

About The Position

Google Research is building the next generation of intelligent systems for Google products, using computer science techniques developed by software developers and research scientists. Research teams collaborate across Google and adapt projects to business needs. As a Research Scientist, you will set up large-scale tests and quickly deploy promising ideas, managing deadlines and deliverables while applying current theories to develop products, processes, and technologies. The work may involve experiments, prototypes, and new architectures addressing problems across computer science. You will also contribute to the research community by sharing and publishing findings, drawing on internal projects and collaborations with partner universities and technical institutes. This role focuses on developing understanding of foundation models and language and multimodal technologies, prototyping new product capabilities, improving quality and cost, and influencing the product roadmap through analysis.

Requirements

PhD degree in Computer Science, a related field, or equivalent practical experience.
2 years of experience in Python and deep learning frameworks (e.g., JAX, Flax, or Gemma).
Experience conducting research and development, including experimental design, implementation, and analysis.
One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, or ICLR).

Nice To Haves

Experience developing multimodal AI models and systems.
Experience fine-tuning and post-training LLMs.
Experience developing generative AI architectures, techniques, and agentic AI solutions.
Experience with multimodal learning that integrates information from different data types, such as vision, audio, and text.
Proven expertise working with, tuning, and prototyping vision-language models (VLMs) using modern strategies.
Strong interest in and awareness of AI alignment, safety, responsibility, and the AI landscape, with enthusiasm for cross-disciplinary collaboration.

Responsibilities

Develop a deep understanding of foundation model, language, and multimodal technologies and how to apply them in the product context.
Prototype new (“zero-to-one”) features and capabilities, and partner with teammates to bring them into production.
Improve product quality and cost optimization through novel approaches and the generation of novel datasets.
Collaborate within and outside the team.
Influence the product roadmap through quantitative and qualitative analysis.
Set up large-scale tests and deploy promising ideas while managing deadlines and deliverables.
Share and publish research findings.