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Microsoft Research Intern - Post-Transformer United States, Washington 607358081
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is seeking summer Research Interns to collaborate with machine learning researchers across MSR and various product teams to build the next generation of models beyond transformer architectures, with a focus on efficiency and robustness. As a Research Intern, you will explore novel model architectures, develop training strategies, and work on post-training alignment and task-specific fine-tuning. Our goal is to deepen the understanding of model learning dynamics, enhance knowledge abstraction, boost overall performance, and mitigate vulnerabilities such as jailbreaking.
- Currently enrolled or accepted in a PhD program in Computer Science, Software Engineering, Electrical Engineering, or a related STEM field.
- At least 1 year of experience in conducting research and authoring peer-reviewed publications.
Other Requirements
- Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship.
- In addition to the qualifications below, you’ll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter.
- Experience in training language models with 7-32B parameters.
- Experience with post-training alignment and fine-tuning.
- Experience with ROCm.
- Proficient written and verbal communication skills.
- Ability to work in a cross-functional, multi-disciplinary environment across research and product teams.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
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