Research Scientist, Gemini Commercial Intelligence, DeepMind

Google•Mountain View, CA

About The Position

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. Join a collaborative and vibrant team of experts in LLMs, multimodal generation/understanding, ML efficiency, and RecSys. We focus on: 1. benchmarking and improving Gemini models across modalities to advance users' commercial journey; 2. self-improving agents to power ML modeling and innovative GenAI experiences across Gemini, Ads, Commerce, and Google. In this role, you’ll be driving research innovations, rapid-prototyping concepts, curating benchmarks, designing experiments, and bridging the path from research to fruition. Some of our current projects focus on these areas: Natural Language & Multimodal Understanding / Generation Planning and reasoning Reinforcement Learning Agents Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google [https://www.google.com/about/careers/applications/benefits/].

Requirements

Bachelor’s degree or equivalent practical experience.
2 years of experience building and shipping technical products.
2 years of experience leading a research agenda.
Experience in the domain area of generative AI and Large Language Models (LLM).

Nice To Haves

Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
3 years of research experience (e.g., model training/deployment, efficiency optimization, data pipeline design, ML infra).
2 years of experience leading research efforts and influencing other researchers.
One or more scientific publication submission(s) for conferences, journals, or public repositories.

Responsibilities

Work with experts on LLMs, multi-modal, recommendation systems, personalization, and ML efficiency.
Drive new research ideas from conception, experimentation, to production in a rapidly shifting landscape.
Drive project work by defining the data structure, framework, design, and evaluation metrics for research solution development and implementation. Identify timelines and obtain resources needed.
Identify new and upcoming research areas by interacting with potential external and internal collaborators. Help in developing long-term research strategy and plans to expand the impact of Google research.