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Researcher - Accelerated Neural Technology
4 months ago
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
