PhD AI Research Intern, 2026 Summer U.S.
Atlassian is a distributed-first company that empowers students through its Intern program, offering hands-on technical training and mentorship. As a PhD AI Research Intern, you will work on advanced machine learning and artificial intelligence technologies, contributing to the development of state-of-the-art AI solutions for enterprises.
Responsibilities
- Collaborate cross-functionally with Research Scientists and Machine Learning Engineers to design, implement, and evaluate experiments that advance the performance, efficiency, and scalability of modern ML and LLM systems for our AI products
- Curate, preprocess, and manage large-scale datasets for training and evaluation, ensuring data quality, diversity, and reproducibility across experiments
- Conduct continued training, fine-tuning, and alignment of large language models for specialized applications such as conversational AI, summarization, generative search, and multimodal agents
- Evaluate cutting-edge ML algorithms through rigorous experimentation and provide detailed analyses highlighting performance insights, failure modes, and opportunities for improvement
- Contribute to publications and presentations at internal workshops or top-tier academic venues, helping to drive innovation in Enterprise AI and large-scale ML systems
Skills
- Completed Bachelors degree in Computer Science or a related field
- Currently pursuing a PhD in Computer Science or a related field at any stage of your doctoral studies. We welcome applications from candidates in all years of their PhD program, including those in the early stages. Degree completion date cannot be earlier than September 2026 - June 2027
- Strong foundation in AI/ML, LLMs, modeling and/or optimization techniques
- 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
- Having publications in top-tier AI conferences or journals will be considered an asset or a plus. Include a publications list (if applicable) to help us assess depth of research and systematic thinking
- Strong communication skills to articulate complex ideas and collaborate with multidisciplinary teams
Benefits
- Health and wellbeing resources
- Paid volunteer days
Company Overview
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