Researcher - Accelerated Neural Technology

Responsibilities:

• Contributing to the synthesis of new large language models to improve the performance of generative AI, directions include but are not limited to: generative AI, generative models, low cost deployment, large language models, neural compression, efficient computing
• Proposing and developing advanced AI/ML with accelerated training and inference to address the real-world problems
• Communicating with other researchers in other teams to find out their challenges, and solving them using AI/ML tools
• Translating fundamental challenges in mathematical problem and transform them into efficient executable codes
• Conducting experiments on large-scale data sets to verify and evaluate the proposed ideas and solutions
• Keeping track of the latest progresses in the (selected) AI/ML areas: generative AI, generative models, large language models, neural compression, efficient computing
• Proposing high-impact intellectual properties (e.g., patents); publishing or contributing to the publishing of research papers in top-tier AI/ML venues such as NeurIPS, ICML, ICLR, AAAI, AISTAT, ACL, EMNLP, etc.

What you’ll bring to the team:

• A Ph.D. degree in Computer Science, Statistics, Applied Mathematics, Electrical and Computer Engineering, Telecommunication, or a related field
• Experience of GitHub and open-source development
• 2+ years of work experience in large language models is an asset
• Publications in high-quality AI/ML venues (e.g., NeurIPS, ICML, ICLR, AAAI, AISTAT, ACL, EMNLP)
• Strong AI/ML coding skills in Python; experienced with Pytorch
• Award-winning experience in international competitions is an asset
• Good communication skills, willingness to collaborate and self-motivated