Research Scientist, Recommendation Systems, DeepMind

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.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $253000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Drive new research ideas from conception and experimentation through to production.
• Drive cross-functional projects and collaborate effectively across organizational boundaries.
• Invent novel solutions to open-ended problems.
• Be flexible, adaptable, and comfortable pivoting when ideas don’t work out.

Minimum qualifications:

• PhD in Machine Learning, Computer Science, or a relevant field or equivalent practical research experience.
• 2 years of experience in LLM post-training algorithms and infrastructure, with a focus on JAX.

Preferred qualifications:

• A proven track record of research excellence with one of the publications at venues like NeurIPS, ICML, ICLR, or significant industry contributions, ranging from recent graduates to experienced researchers.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA.