AI Research Intern (PhD), 2027 Summer U.S.

Atlassian•San Francisco, CA

3d•Hybrid

About The Position

Atlassian is hiring a PhD Research Intern for its Machine Learning Research team. The internship focuses on advanced machine learning and artificial intelligence, including large language models, generative AI, conversational agents, and AI optimization. Interns contribute to foundational research and practical applications, including training, evaluating, and optimizing inference for AI models intended to serve Atlassian customers. They collaborate with experienced researchers and engineers on research and development that addresses real-world Enterprise problems and improves teamwork and collaboration. The role is preferred to be co-located in Seattle or in the Pacific Standard Timezone. The paid internship typically lasts 12 weeks between May/June and August/September 2027. Atlassian operates as a distributed-first company, and interviews are conducted virtually.

Requirements

Completed a bachelor's degree in Computer Science or a related field.
Currently pursuing a PhD in Computer Science or a related field; candidates at any stage of doctoral study are welcome.
Degree completion date cannot be earlier than September 2026 or later than June 2027.
Strong foundation in AI/ML, LLMs, modeling, and/or optimization techniques.

Nice To Haves

Solid grasp of algorithms and data structures.
Proficiency in Python and ability to write clean, efficient, and well-documented code.
Experience with large-scale datasets, including preprocessing, augmentation, and scaling techniques.
Experience managing data with Python libraries such as NumPy, Pandas, and Matplotlib; using models from Hugging Face; and applying machine learning and deep learning frameworks such as PyTorch.
Exposure to natural language processing and computer vision.
Familiarity with state-of-the-art machine learning and AI research, demonstrated through coursework, publications, or projects.
Publications in top-tier AI conferences or journals; include a publications list if applicable.
Strong communication skills and ability to articulate complex ideas and collaborate with multidisciplinary teams.

Responsibilities

Collaborate with Research Scientists and Machine Learning Engineers to design, implement, and evaluate experiments that advance the performance, efficiency, and scalability of ML and LLM systems for AI products.
Curate, preprocess, and manage large-scale training and evaluation datasets, ensuring data quality, diversity, and reproducibility.
Conduct continued training, fine-tuning, and alignment of large language models for applications such as conversational AI, summarization, generative search, and multimodal agents.
Evaluate ML algorithms through rigorous experiments and analyze performance, failure modes, and opportunities for improvement.
Contribute to publications and presentations at internal workshops or academic venues.