PhD AI Research Intern, 2026 Summer U.S.
Atlassian
PhD AI Research Intern, 2026 Summer U.S.
Job Description
PhD AI Research Intern, 2026 Summer U.S.
📋 Job Overview
Join Atlassian's Machine Learning Research team as a PhD Research Intern to work on advanced AI technologies, including LLMs and Generative AI. You will collaborate with experienced researchers and engineers to develop state-of-the-art AI solutions for Enterprises, gaining hands-on experience in both foundational research and practical applications.
📍 Location: Seattle, United States
🏢 Category: Interns
📅 Posted: 2025-12-09 06:19 PM
🎯 Key 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.
✅ Required Qualifications
- 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. Degree completion date cannot be earlier than September 2026 - June 2027.
- Strong foundation in AI/ML, LLMs, modeling and/or optimization techniques.
⭐ Preferred Qualifications
- 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.
🛠️ Required Skills
- Machine Learning
- Artificial Intelligence
- Large Language Models
- Generative AI
- Conversational Agents
- AI Optimization
- Algorithms
- Data Structures
- Python
- Data Preprocessing
- Data Augmentation
- Data Scaling
- NumPy
- Pandas
- Matplotlib
- Hugging Face
- PyTorch
- Natural Language Processing
- Computer Vision
- Communication Skills
🎁 Benefits & Perks
- Health and wellbeing resources
- Paid volunteer days
Locations
- Seattle, United States
Salary
Estimated Salary Rangemedium confidence
120,000 - 180,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learningintermediate
- Artificial Intelligenceintermediate
- Large Language Modelsintermediate
- Generative AIintermediate
- Conversational Agentsintermediate
- AI Optimizationintermediate
- Algorithmsintermediate
- Data Structuresintermediate
- Pythonintermediate
- Data Preprocessingintermediate
- Data Augmentationintermediate
- Data Scalingintermediate
- NumPyintermediate
- Pandasintermediate
- Matplotlibintermediate
- Hugging Faceintermediate
- PyTorchintermediate
- Natural Language Processingintermediate
- Computer Visionintermediate
- Communication Skillsintermediate
Required Qualifications
- Completed Bachelors degree in Computer Science or a related field. (experience)
- Currently pursuing a PhD in Computer Science or a related field at any stage of your doctoral studies. Degree completion date cannot be earlier than September 2026 - June 2027. (experience)
- Strong foundation in AI/ML, LLMs, modeling and/or optimization techniques. (experience)
Preferred Qualifications
- Exhibit a solid grasp of algorithms and data structures. (experience)
- Demonstrate proficiency in Python programming and ability to write clean, efficient, and well-documented code. (experience)
- Experience working with large-scale datasets, including data preprocessing, augmentation, and scaling techniques. (experience)
- 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. (experience)
- Demonstrated exposure to natural language processing (NLP) and Computer Vision (CV) (experience)
- Familiarity with state-of-the-art research in machine learning and AI, as evidenced by relevant coursework, publications, or projects. (experience)
- 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. (experience)
- Strong communication skills to articulate complex ideas and collaborate with multidisciplinary teams. (experience)
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.
Benefits
- general: Health and wellbeing resources
- general: Paid volunteer days
Tags & Categories
PhD AI Research Intern, 2026 Summer U.S.
Atlassian
PhD AI Research Intern, 2026 Summer U.S.
Job Description
PhD AI Research Intern, 2026 Summer U.S.
📋 Job Overview
Join Atlassian's Machine Learning Research team as a PhD Research Intern to work on advanced AI technologies, including LLMs and Generative AI. You will collaborate with experienced researchers and engineers to develop state-of-the-art AI solutions for Enterprises, gaining hands-on experience in both foundational research and practical applications.
📍 Location: Seattle, United States
🏢 Category: Interns
📅 Posted: 2025-12-09 06:19 PM
🎯 Key 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.
✅ Required Qualifications
- 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. Degree completion date cannot be earlier than September 2026 - June 2027.
- Strong foundation in AI/ML, LLMs, modeling and/or optimization techniques.
⭐ Preferred Qualifications
- 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.
🛠️ Required Skills
- Machine Learning
- Artificial Intelligence
- Large Language Models
- Generative AI
- Conversational Agents
- AI Optimization
- Algorithms
- Data Structures
- Python
- Data Preprocessing
- Data Augmentation
- Data Scaling
- NumPy
- Pandas
- Matplotlib
- Hugging Face
- PyTorch
- Natural Language Processing
- Computer Vision
- Communication Skills
🎁 Benefits & Perks
- Health and wellbeing resources
- Paid volunteer days
Locations
- Seattle, United States
Salary
Estimated Salary Rangemedium confidence
120,000 - 180,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learningintermediate
- Artificial Intelligenceintermediate
- Large Language Modelsintermediate
- Generative AIintermediate
- Conversational Agentsintermediate
- AI Optimizationintermediate
- Algorithmsintermediate
- Data Structuresintermediate
- Pythonintermediate
- Data Preprocessingintermediate
- Data Augmentationintermediate
- Data Scalingintermediate
- NumPyintermediate
- Pandasintermediate
- Matplotlibintermediate
- Hugging Faceintermediate
- PyTorchintermediate
- Natural Language Processingintermediate
- Computer Visionintermediate
- Communication Skillsintermediate
Required Qualifications
- Completed Bachelors degree in Computer Science or a related field. (experience)
- Currently pursuing a PhD in Computer Science or a related field at any stage of your doctoral studies. Degree completion date cannot be earlier than September 2026 - June 2027. (experience)
- Strong foundation in AI/ML, LLMs, modeling and/or optimization techniques. (experience)
Preferred Qualifications
- Exhibit a solid grasp of algorithms and data structures. (experience)
- Demonstrate proficiency in Python programming and ability to write clean, efficient, and well-documented code. (experience)
- Experience working with large-scale datasets, including data preprocessing, augmentation, and scaling techniques. (experience)
- 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. (experience)
- Demonstrated exposure to natural language processing (NLP) and Computer Vision (CV) (experience)
- Familiarity with state-of-the-art research in machine learning and AI, as evidenced by relevant coursework, publications, or projects. (experience)
- 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. (experience)
- Strong communication skills to articulate complex ideas and collaborate with multidisciplinary teams. (experience)
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.
Benefits
- general: Health and wellbeing resources
- general: Paid volunteer days
Tags & Categories