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SimplifyJobs/Summer2027-Internships

Summer 2027 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC.

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SimplifyJobs/Summer2027-Internships has 48k+ stars and 3k+ forks on GitHub, is written in Python, and was last pushed on Oct 18, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 1 hour ago
Type:Curated List / Learning ResourceCategory(s):Education & Research ToolsGeneral Awesome Lists & DirectoriesScience & Industry
Added to GitGenius on August 31st, 2026
Created on May 23rd, 2020
Open Issues & Pull Requests: 114 (+0)
GitHub issues: Enabled
Number of forks: 3,258
Total Stargazers: 48,038 (+0)
Total Subscribers: 1,868 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 0.0 hours
Mean response time: 2.2 days
90th percentile: 3.1 days
Tracked items: 957

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Maintainer activity

6 people did triage or write work on this repository in the last 12 months.

Counts unlabeled, assigned, unassigned, milestoned, demilestoned, locked, unlocked over the last 12 months. These are issue and pull request events that require triage or write permission. Commits and code review are not counted. labeled and renamed are excluded because GitHub issue forms record the issue author as the actor. Figures from October 18, 2026. This count is not comparable across projects: each project's automation decides which of these events a person emits. How this is counted.

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 98% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "approved" is answered fastest, typically in under an hour, while "enhancement" waits about 3 days. 44% of tracked open issues have had no activity in three months. 94% of issues opened in the past year have since been closed.

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Issue Activity (beta)

Open issues: 111
New in 7 days: 4
Closed in 7 days: 0
Avg open age: 46 days
Stale 30+ days: 101
Stale 90+ days: 49

Recent activity

Opened in 7 days: 4
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 1

Top labels

  • approved (5,008)
  • edit_internship (3,198)
  • new_internship (2,087)
  • duplicate (97)
  • bulk_mark_inactive (67)
  • misc (35)
  • enhancement (20)

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Detailed Description

Summer2027-Internships is a curated job listing repository that aggregates summer internship postings across software engineering, data science, AI, quantitative finance, product management, and hardware engineering roles.

The repository addresses the challenge of finding and tracking tech internship opportunities by centralizing postings from multiple employers in one searchable location. Rather than visiting individual company career pages, students and job seekers can browse categorized listings updated daily. The approach relies on community contributions and active maintenance by the Pitt Computer Science Club and Simplify to keep the catalog current and comprehensive.

This repository suits students and early-career professionals searching for summer internships in technical fields. It works best for those who want a single source of truth rather than monitoring dozens of company websites independently. The tool provides filtering by role type, sponsorship eligibility, and company tier, helping candidates quickly identify positions matching their qualifications and visa requirements. A companion service called SWEList offers email notifications for new postings, addressing the friction of manual daily checking.

The project maintains daily updates through active coordination between its two maintaining organizations. Community members can submit new internship postings via GitHub issues following established contribution guidelines. The repository includes supplementary resources such as archived listings from previous years, off-season internship alternatives, and related job boards for new graduates, indicating ongoing expansion of scope based on user needs.