Improving efficiency of Large Language Models (LLMs) to deploy large models, specifically in resource-constrained environments, at Microsoft
Requirements
- At least 1 year of experience working on AI/Machine Learning
- Hands-on experience with ML tools and frameworks such as Pytorch
- Experience training and evaluating models
- Publication track record in ML conferences
- Ability to collaborate effectively with other researchers and product teams
- Currently enrolled in a PhD program in Computer Science or a related field
- Experience with designing and implementing systems optimizations
Responsibilities
- Design training algorithms to improve the quality/efficiency trade-offs of large language models
- Apply training algorithms to improve the quality/efficiency trade-offs of large language models
- Design new algorithms for quantized model fine-tuning
- Leverage training to improve the token efficiency of reasoning models
- Propose and implement systems optimizations to scale training under resource constraints
- Present findings and contribute to the vibrant life of the community
- Collaborate with other Research Interns and researchers
Other
- Currently enrolled in a PhD program in Computer Science or a related field
- Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship
- Submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples
- Ability to collaborate effectively with other researchers and product teams
- Must be able to work in a team environment
