AI Research Intern, 2025 Summer U.S.

Overview

Working at Atlassian

Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.

Join our cutting-edge Machine Learning Research team at Atlassian as a PhD Research Intern, where you'll have the opportunity to work on advanced machine learning (ML) and artificial intelligence (AI) technologies, particularly focusing on areas such as Large language models (LLMs), Generative AI, Conversational Agents, and AI Optimization. You’ll be part of a team that pioneers innovations to address complex real-world problems, developing state-of-the-art AI solutions that will ultimately drive impact for Enterprises.

As a PhD intern, you will gain hands-on experience in both foundational research and practical applications, contributing to the training, evaluation and optimized inferencing of AI models that could be used by millions of customers. You will collaborate closely with experienced researchers and engineers to push the boundaries of what’s possible with AI, while gaining invaluable insights into industrial research and development.

Why Join Us

This internship is designed for individuals passionate about exploring new frontiers in AI and machine learning research. You’ll work in a stimulating environment with some of the brightest minds in the field, gaining exposure to both academic and applied research challenges. We are committed to providing a supportive and inclusive work environment where interns are empowered to contribute significantly to ongoing research that improves teamwork and collaboration in an Enterprise.

Application Process

If you're passionate about AI and eager to contribute to transformative technology, we encourage you to apply. Please submit your resume and a brief cover letter detailing your relevant experience and interest in the role.

Responsibilities

• Collaborate with Research Scientists and Machine Learning Engineers to contribute to the design and execution of research experiments aimed at improving the performance, efficiency, and scalability of ML models.

• Curate, preprocess, and manage large datasets for training and evaluation of machine learning models, including LLMs.

• Execute continued training and alignment of LLMs for specific applications such as conversational AI, summarization and multi-modal agents.

• Evaluate advanced ML algorithms, providing detailed reports on model performance, strengths, and areas of improvement.

• Publish research in internal and external industry workshops and in top-tier academic journals or conferences to spearhead innovation in the field of Enterprise AI and ML.

Qualifications

Required Qualifications

• Completed Bachelors degree in Computer Science or a related field.

• Currently pursuing a PhD in Computer Science or a related field with an anticipated degree completion date between September 2025 - June 2026.

• Strong foundation in AI/ML, LLMs, modeling and/or optimization techniques.

Desired Skills and Attributes

• Exhibit a solid grasp of algorithms and data structures.

• Demonstrate proficiency in Python programming and ability to write clean, efficient, and well-documented code.

• Experience working with large-scale datasets, including data preprocessing, augmentation, and scaling techniques.

• Has expertise in managing data using Python libraries such as NumPy, Pandas, Matplotlib, in addition to leveraging models from Hugging Face and has practical knowledge of applied machine learning and deep learning frameworks, like PyTorch.

• Demonstrated exposure to natural language processing (NLP) and Computer Vision (CV)

• Familiarity with state-of-the-art research in machine learning and AI, as evidenced by relevant coursework, publications, or projects.

• Strong communication skills to articulate complex ideas and collaborate with multidisciplinary teams.

Compensation

At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. In the United States, we have three geographic pay zones. For this role, our current base