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Research Software Engineer - Efficient Large Language Models



Software Engineering
Posted on Thursday, January 4, 2024
At IBM, work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so, lets talk.

Your Role and Responsibilities
Are you excited about the latest advances in Large Language Models? Are you interested in advancing efficiency of large language models, publishing your work in the most prestigious AI conferences in the world, and making your code open source? How about working closely with top-notch MIT faculty, students, and IBM scientists in a flexible and fun environment? Are you passionate about opportunities to bridge your scientific work to real-world impact? If you answered yes to these questions, then you should apply to our research software engineer position at IBM Research. We are seeking a talented and highly motivated engineer with background in natural language processing to join our team. You will be responsible to conduct cutting-edge research on efficient training and inference of large language models, developing prototype solutions to real-world problems, and publishing papers in top-quality conferences. We believe efficiency is key to enable state-of-the-art language models work on a variety of devices, make a real impact in the world and bring research to practice.

Required Technical and Professional Expertise
  • Hands-on experience in natural language processing and deep learning
  • Strong programming and software engineering skills
  • Great problem solving skills, with a strong desire for quality and engineering excellence
  • Ability to quickly prototype ideas and use creative approaches for solving complex problems

Preferred Technical and Professional Expertise

  • Publications in top AI conferences
  • Experience with training and inference of language models for key NLP tasks