Research Intern - Training-Time Provenance (Data Dignity)
Mountain View, California, United States
Microsoft
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Training-time provenance is a research effort on estimating the influence of specific training data on outputs of large language models (LLMs). Current neural network architectures are opaque in terms of providing sources for their generations, and there are at least two good reasons to change this:
- “X-ray” into intent, so that we can detect bad human actors or dangerous AI activity by identifying the most influential source documents related to a given model output. For instance, sneaky prompts might invoke articles about bomb making that could evade guardrails otherwise. This will be a deeper method of countering this type of danger than others currently in use.
- “Data dignity”, meaning incentives, recognition, and potentially pay for people who contribute certain valuable data to unforeseen kinds of models we will want in the future, assuming the future will surprise us fundamentally. The goal is to foster new classes of creative professionals where possible, instead of relying solely on ideas like Universal Basic Income in the event of a future with very high-functioning large models.
We are attempting to demonstrate that LLMs can be trained in such a way that influence of specific training data on generated outputs can be efficiently and usefully estimated. You can read more about “Data dignity” in the article: There is no A.I. (The New Yorker).
Responsibilities
Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world’s best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer.
For this Research Internship (summer 2025), we are seeking PhD students with a passion for fundamental Deep Learning research, particularly those with experience in training LLMs and other large AI models. The Research Intern's responsibilities will include (1) training small language models with novel schemes preserving provenance of data, (2) experimenting with these models to test their performance and reliability.
Qualifications
Required Qualifications
- Currently enrolled in a PhD program in Computer Science or a related STEM field. Exceptional candidates enrolled in a master’s program might also be considered.
- At have at least 2 years of research experience, including peer-reviewed publications, researching a topic closely related to the above description, such as natural language processing, deep learning, generative models, approximation methods, etc.
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.
Preferred Qualifications
- Demonstrated ability to develop original research agendas.
- Ability to collaborate effectively with other researchers and product development teams.
- Experience in training large AI models.
- Experience in approximation methods for deep learning systems.
- Proficient interpersonal skills, cross-group, and cross-culture collaboration.
- Ability to think unconventionally to derive creative and innovative solutions.
Applied Sciences IC2 : The base pay range for this internship is USD $5,460 -$10,680 per month.
There is a different range applicable to specific work locations, with the San Francisco Bay area and New York City Metropolitan area, and the base pay range for this role in those locations is USD $7,040 -$11,640 per month.
Applied Sciences IC3 : The base pay range for this internship is USD $6,550 -$12,880 per month.
There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $8,480 - $13, 920 per month.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-intern-pay
Microsoft accepts applications and processes offers for these roles on an ongoing basis.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Tags: Architecture Computer Science Deep Learning Economics Generative modeling LLMs NLP PhD Research STEM
Perks/benefits: Career development Medical leave
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