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  • Research Intern - AI Evaluation and Alignment

    Microsoft Corporation (Redmond, WA)



    Apply Now

    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.

     

    Microsoft Research and Copilot Studio team are seeking Research Interns to help advance the quality, reliability and evaluation of Large Language Model (LLM)-based systems. Research Interns will collaborate with applied scientists and engineers to explore new machine learning methods that improve how Artificial Intelligence (AI) systems assess and align with human expectations.

    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.

    Additional Responsibilities

    We are looking for candidates with proficient intellectual curiosity and passion to solve real-world problems using machine learning. Responsibilities include:

     

    + Co-developing a research project in collaboration with the supervisor and research mentors.

    + Designing and implementing machine learning approaches, including training and fine-tuning using real-world datasets.

    + Developing evaluation frameworks and benchmarking methods to assess model quality, robustness, and generalization.

    + Presentation and communication of research findings

    Qualifications

    Required Qualifications

    + Currently enrolled in a PhD program in Statistics, Computer Science, Physics, Operations Research, or a related technical field.

    + At least 1 year of hands-on experience working on LLM-related projects (e.g., prompt engineering, building and evaluating LLM-based systems, rewards modeling etc.).

    + At least 1 year of experience coding in Python.

    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.

     

    Additional Information

    Please submit a list of projects you worked on in the last 2 years with the following information:

    + Start and end date for the project.

    + Brief overview of what the project is about.

    + What you did on the project.

    + What technologies you used for the project.

     

    You can upload documents by going to your profile on the career site and clicking on the **Resume Manager** tab in the top right of the page, and from there selecting **Other Documents.**

     

    If you are having trouble submitting your application, please go to the bottom of the page and click "Support" and fill out the requested information.

    Preferred Qualifications

    + Prior experience in reward models for large language models or LLM-as-a-Judge.

    + Strong experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with software engineering best practices (e.g. git).

    + Experience with LLM post-training and evaluation or LLM-based judge systems.

    + Research experience demonstrated through publications or projects.

    + Ability to work independently in ambiguous or rapidly evolving situations and collaborate effectively across disciplines.

     

    The base pay range for this internship is USD $6,710 - $13,270 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 $8,760 - $14,360 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

     

    Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

     

    This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

     

    Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations. (https://careers.microsoft.com/v2/global/en/accessibility.html)

     


    Apply Now



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