Senior Research Scientist, Beam

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. 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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google .

Develop deep understanding of foundation model, language and multi-modal technologies and approach to applying them in the product’s context. Prototype new (“zero-to-one”) features and capabilities, and partner with teammates to land them in production. Improve product quality and cost optimization via novel approaches and generation of novel data sets. Collaborate within the team and outside the team. Influence product roadmap via quantitative and qualitative analysis.

Minimum qualifications: 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 of more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.). Preferred qualifications: Experience in developing multimodal AI models and systems. Experience fine-tuning and post-training LLMs. Experience with developing generative AI architectures, techniques, and agentic AI solutions. Experience with multimodal learning, integrating information from different data types (e.g., vision, audio, text). Proven expertise in working with, tuning, and prototyping vision-language models (VLMs) using modern strategies. Strong interest in and awareness of the AI alignment, safety, responsibility, and landscape, with an excitement to collaborate across disciplines.