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The File Solutions team provides a set of fully managed file services for Enterprise and HPC and AI/ML customers addressing workloads (e.g., SAP, GKE applications, etc.). The team facilitates seamless migration to cloud, hybrid cloud solutions, and seamless integration with other File solutions and Google Cloud Platform (GCP) solutions and services.

The team's goal is to be the authoritative one stop shop for all file solutions in GCP, serving large-scale strategic customers and managing customer data, while maintaining the highest performance, scale, reliability, usability, quality, and observability as well as ownership of the whole file portfolio, whether built from the ground up internally or via integration with third-party and open source technologies.

Google Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Googles cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities
Drive the technical decision making and prioritization across File Solutions integration with external/internal products (e.g., Filestore, NetApp, PFS/DAOS) and infras to create a superb experience to our customers covering all the workloads and needs.
Guide a team of engineers based in India, Tel Aviv, and Kirkland through technical design directions for creating the best file solutions for our customers achieving high quality, reliability, and development velocity.
Collaborate with engineering and product leadership on setting priorities and building strategic roadmap as well as multiple local and remote teams serving the product portfolio (e.g., UX, UI etc.).
Build relationships, and collaborate with and work closely with various Developer partners and external companies we integrate with to create the best solution including all the technical aspects.

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.

Our team is committed to developing advanced methodologies tailored specifically for multilingual environments. We focus on pre-training multilingual models, enhancing the quality of multilingual instruction-tuning datasets, refining multilingual evaluation processes, boosting knowledge transfer across languages, and optimizing multilingual tokenization among other initiatives.

The Technology & Society organization connects research, people, and ideas across Google and Alphabet to help shape and advance our most ambitious technology innovations and initiatives and their impact on users and society for the better, and responsibly. In addition, we also aim to share perspectives, engage, and collaborate with others externally on technology related issues and opportunities for society.

Responsibilities
Author research papers to share and generate impact of research results across the team and in the research community.
Research and develop technology for improving multilingual Large Language Models (LLM) such as instruction-tuning, pre-training, multilingual reasoning.
Research and develop technology for pre-training LLMs for languages other than English.
Collaborate with other research teams to expand multilingual LLM technology.
Collaborate with Google first-party partner teams to deliver new multilingual technologies to production.