Machine Learning Intern, 2027 Summer U.S.

Reposted Yesterday
2 Locations
In-Office
45-61 Hourly
Internship
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Atlassian provides tools to help every team unleash their full potential.
The Role
Build and evaluate applied machine learning and Generative AI solutions for product and business problems. Interns will contribute to models, agents, retrieval, experimentation, evaluation, and prototyping with mentorship from experienced engineers. Responsibilities include translating business needs into technical projects, analyzing errors and user feedback, measuring outcomes, and clearly documenting findings, trade-offs, limitations, and next steps.
Summary Generated by Built In
Interns | San Francisco, United States | Seattle, United States
Working at AtlassianAtlassians have the flexibility to work where they can collaborate most effectively with their team, whether at home, one of our global offices, or both. We hire in any country where we have a legal entity. Learn how we work at

Skills Required

  • Currently enrolled full-time in a Master's degree program in a quantitative field such as Computer Science, Machine Learning, AI, Data Science, Statistics, Mathematics, or a related field.
  • Returning to the degree program after the internship and graduating by August 2028.
  • Strong software engineering fundamentals.
  • Experience with Python, testing, version control, APIs, data structures, and debugging.
  • Hands-on experience building machine learning or AI systems through coursework, research, or industry internships.
  • Experience in areas such as recommendation or ranking, NLP, classification, embeddings, LLM applications, RAG, agents, or model evaluation.
  • Experience using AI-assisted development tools thoughtfully, validating generated code and outputs, and explaining their value and limitations.
  • Strong problem-solving and communication skills.
  • Interest in building reliable and responsible AI/ML solutions.
  • Ability to commit to a 12-week, full-time, 40-hour-per-week Summer 2027 internship.
  • Ability to work from the Seattle or San Francisco hub.

What the Team is Saying

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Atlassian Compensation & Benefits Highlights

  • Parental & Family Support — Parental leave spans 26 weeks for birthing parents and 20 weeks for non-birthing parents, alongside inclusive family-formation benefits such as fertility treatment, adoption, and surrogacy. Additional supports include menopause resources and caregiving-related programs.
  • Retirement Support — Retirement programs include a U.S. 401(k) company match with immediate vesting and multiple contribution options. These are complemented by other financial wellbeing tools like HSAs/FSAs.
  • Healthcare Strength — Medical coverage is paired with mental-health resources, disability and life insurance, and options such as HSA/FSA. Descriptions also point to solid plan choices with access to counseling, coaching, and 24/7 support.

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The Company
HQ: San Francisco, CA
11,000 Employees
Year Founded: 2012

What We Do

Atlassian creates teamwork solutions for high-performing teams. Our portfolio of collaboration and work management software products includes Jira, Confluence, Trello, Loom and Rovo. More than 300,000 businesses worldwide rely on Atlassian’s technology, including 80 percent of Fortune 500 companies. Our solutions support various business teams and they help organizations plan, track, and deliver their biggest ideas together.

Why Work With Us

At Atlassian, we believe we can accomplish so much more together than apart — which is why everything from our tooling — to our distributed workforce — to how our teams are structured is rooted in collaboration. Come join us and help unleash the potential of every team.

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Employees work remotely.

Atlassians have flexibility in where they work to support their family, personal goals, and other priorities. Our approach to distributed work allows us to tap into talent beyond our office locations, and to reimagine how work gets done.

Typical time on-site: None
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