Senior Research Scientist, Multilingual NLP

2 Months ago β€’ 7 Years + β€’ Research & Development

Job Summary

Job Description

Google is seeking a Senior Research Scientist specializing in multilingual NLP for low-resource languages. The role involves developing multilingual LLMs for translation and semantic understanding, building and expanding datasets (including multimodal text and audio), creating novel evaluation datasets, and developing algorithms for LLM training and evaluation. Responsibilities include designing algorithms for model training and prediction, managing experiments on TPUs, writing technical reports and publications, proposing research ideas, providing research leadership, and programming in Python with JAX and PAX. The successful candidate will contribute to Google's portfolio of research projects, collaborating with internal and external teams.
Must have:
  • PhD in CS or related field
  • 7+ years NLP/ML experience
  • Publications in top NLP conferences
  • Python/C++ programming skills
  • Experience with LLMs
  • Algorithm design & TPU experience
Good to have:
  • Innovative research experience
  • Teamwork experience
  • Excellent coding skills
  • Experience with JAX and PAX

Job Details


Minimum qualifications:

  • PhD in Computer Science, a related technical field, or equivalent practical experience.
  • 7 years of experience in NLP, NLU, Machine Learning, LLMs, or a related field.
  • Experience contributing to research communities including publishing in forums (e.g., ACL, EMNLP, NAACL, EACL, COLING, ICLR, AAAI, NeurIPS).
  • Experience with programming languages (e.g., Python or C/C++).

Preferred qualifications:

  • Experience in innovative research.
  • Experience working with a research team.
  • Ability to effectively navigate ambiguity.
  • Excellent coding skills.

About the job

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.

In this role, you will work on multilingual Natural Language Processing (NLP) for low resource languages. This project aims to develop multilingual Large Language Models (LLMs), and their application to translation and semantic understanding tasks. You will build several existing/in-development datasets, and also construct several additional resources, including multimodal text and audio. You will create novel evaluation datasets, compile and create new datasets, and develop algorithms for LLM training and evaluation.

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.

Responsibilities

  • Design algorithms for model training and prediction.
  • Manage experiments on Tensor Processing Unit (TPU) cloud.
  • Write up results in design documents, technical reports, and papers for publication.
  • Propose new research ideas and provide research leadership in the team.
  • Write programs in Python with JAX and PAX.

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