How to Apply to Machine Learning at Berkeley (ML@B)

Updated

ML@B accepts applications at the start of every Fall and Spring semester, and the Apply link on the site is the entry point. The organization describes itself as looking for "excellent student leaders, researchers and builders in the ML space," so the application is aimed at current students who want to contribute to consulting, research, or education work rather than at companies or external researchers.

Who the application is for

ML@B is a student-run non-profit organization at UC Berkeley. Its work spans three areas, and applicants should think about which one fits them:

  • Consulting — teams of experienced members work with companies on ML-powered solutions to multidisciplinary business problems.
  • Research — students and researchers collaborate on original ML research, with support that includes compute resources and funding to attend AI/ML conferences.
  • Education — members create content at levels ranging from a 2-unit DeCal course to high school workshops to a Udacity Nanodegree Program.

The site's recruiting language ("student leaders, researchers and builders") suggests applications are reviewed with an eye toward contribution in at least one of these areas, not a single generic track.

Steps to apply

  1. Check the timing. Applications open at the start of each Fall and Spring semester. If you are outside those windows, plan to apply at the next one rather than expecting a rolling process.
  2. Go to the Apply page. The site's navigation includes an Apply link in both the header and footer menus, alongside Home, About, Education, Partnerships, Research, Students, Blog, and Contact.
  3. Prepare to describe your fit. Based on the site's stated interests, be ready to show work or experience in ML and to explain whether you lean toward building (consulting), research, or teaching.
  4. Use Contact if you have questions. The site offers a Contact option for reaching the organization before or alongside applying.

What to verify before you start

The site does not publish application deadlines, interview formats, or selection rates, so treat the semester-start timing as the only confirmed scheduling detail. If a specific deadline matters to you, use the Contact link rather than assuming a date.

Common sticking points

  • Applying mid-semester. The stated cycle is start-of-semester only; a mid-term application may not be reviewed until the next cycle.
  • Assuming it is a course enrollment. ML@B is a student organization, not a class. Its DeCal is one education offering, but joining the organization is a separate application.
  • Confusing the audiences. The Partnerships pages are for companies seeking consulting, industry, or research partnerships. Students should use the Apply path instead.

For students deciding whether to apply, the clearest signal is the organization's own framing: it wants people who will help build "one of Cal's most vibrant ML communities." If you can point to ML work you have done and a direction among consulting, research, or education you want to pursue, you have what the application is asking for.