Research Intern - Training-Time Provenance (Data Dignity)

1 Month ago • 2 Years + • Research & Development • $65,520 PA - $128,800 PA

Job Summary

Job Description

This research internship focuses on training-time provenance for Large Language Models (LLMs), aiming to understand and estimate the influence of specific training data on model outputs. The research addresses "data dignity" by exploring ways to incentivize and recognize data contributors. Responsibilities include training small LLMs with novel provenance-preserving schemes, experimenting with model performance and reliability, and collaborating with researchers. The internship involves contributing to the development of methods to 'X-ray' model intent to detect malicious activity and promote ethical AI practices. Candidates should possess a strong background in deep learning, natural language processing, and generative models.
Must have:
  • PhD in CS or related STEM field
  • 2+ years research experience
  • Peer-reviewed publications
  • Experience with NLP, deep learning, generative models
  • Training small LLMs with novel schemes
  • Experimenting with model performance and reliability
Good to have:
  • Experience training large AI models
  • Experience in approximation methods for deep learning
  • Ability to develop original research agendas
  • Collaboration skills
Perks:
  • Industry-leading healthcare
  • Educational resources
  • Discounts on products and services
  • Savings and investments
  • Maternity and paternity leave
  • Generous time away
  • Giving programs
  • Networking opportunities

Job Details

Overview

Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment.

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:

  1. “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.
  2. “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).

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: 

Microsoft accepts applications and processes offers for these roles on an ongoing basis.

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. 

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Opportunities to network and connect

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