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.
Modern Large Language Models (LLMs) are required to display increasingly complex capabilities, which lend themselves naturally to modeling using reinforcement learning techniques. In this role, you will research new algorithmic approaches for training LLMs. The work should result in impact on top google products, like Gemini, Search and Cloud, as well as support research in the field.
Google Research is building the next generation of intelligent systems for all Google products. To achieve this, were 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.
Responsibilities
Research and develop RL algorithms for improving various Large Language Model (LLM) capabilities.
Train, evaluate and analyze models.
Collaborate with partners and product functions to deliver new model capabilities to production.
Collaborate with other research teams to expand LLM technology.
Requirements: Minimum qualifications:
PhD degree in Computer Science, a related field, or equivalent practical experience.
One or more scientific publication submission(s) for conferences, journals, or public repositories.
Preferred qualifications:
2 years of coding experience.
Experience with modern LLMs and generative models.
Experience with Reinforcement Learning.
Publication track record in related GenAI fields.
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