Research Intern, Training Methods for LLM Efficiency
Quick summary
- Work type
- On-site
- Location
- —
- Employment
- Intern
- Posted
- 2 days ago
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This listing doesn't post a salary. Most similar roles pay $167,500–$248,587.
Based on 240 similar postings.
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About Microsoft
Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing
Microsoft currently has 622 open roles on FindRole.
Listed pay typically runs $119,800–$234,700 across 559 roles with salary data.
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At a glance
TL;DR · Research Intern, Training Methods for LLM Efficiency
As a Research Intern at our cutting-edge AI lab, you will join a dynamic team of PhD students and senior researchers focused on enhancing the efficiency of Large Language Models (LLMs) through innovative training algorithms. Your primary responsibilities include designing new methods for quantized model fine-tuning, improving token efficiency in reasoning models, and implementing systems optimizations to scale training under resource constraints. You will work with state-of-the-art tools like PyTorch and contribute to a vibrant research community by publishing your findings in leading ML conferences. This role demands hands-on experience in AI/Machine Learning, proficiency in Python, and strong collaboration skills to bridge the gap between theoretical advancements and practical applications in resource-limited settings.
What you'll do
- Design new algorithms for quantized model fine-tuning to enhance efficiency.
- Investigate methods to improve token efficiency of reasoning models during training.
- Propose systems optimizations to scale training under resource-constrained conditions.
- Apply advanced training techniques to large language models to optimize performance.
- Implement and evaluate the impact of proposed improvements on model quality.
What we're looking for
- Currently enrolled in a PhD program in Computer Science or related field.
- At least 1 year of experience working on AI/Machine Learning.
- Hands-on experience with ML tools and frameworks like Pytorch.
- Experience training and evaluating machine learning models.
- Publication record in Machine Learning conferences.
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