AI Researcher

Overview: Working at Atlassian

Atlassian’s Grad++ program offers a unique blend of hands-on technical training, professional growth, dedicated mentorship, and strong social connections. This comprehensive approach is designed to empower students, ensuring a successful and impactful career at Atlassian from day one.

This AI Researcher role is preferred to be co-located to a specific location within the Pacific Standard Timezone, or for candidates located within the PST timezone itself.

Your Future Team

Atlassian's core mission is to unleash the potential of every team. Our software products facilitate collaboration across the globe for all types of work, making collective achievement possible. AI/ML is pivotal in transforming how teams plan, track, and deliver work, significantly boosting productivity across our product portfolio. Join our Machine Learning team to advance this mission by leveraging AI to make teams more efficient.

About the Role: Responsibilities of an AI Researcher

As an AI Researcher in our cutting-edge Machine Learning Research team, you will focus on advanced Machine Learning (ML) and Artificial Intelligence (AI) technologies. Your work will particularly emphasize Large Language Models (LLMs), Generative AI, Search, Conversational Agents, and AI Optimization. This role involves pioneering innovations to solve complex real-world challenges, developing state-of-the-art AI solutions that will ultimately impact enterprise clients.

Your daily responsibilities include designing system and model architectures, conducting rigorous experimentation, and performing thorough model evaluations. You will be responsible for applying AI/ML to various product problems to enhance Atlassian products and actively contribute to the Atlassian Intelligence features.

Qualifications

To be successful as an AI Researcher, candidates should meet the following qualifications:

Required Qualifications

• Bachelor's degree or above in Computer Science or a relevant technical field.
• Currently enrolled full-time in a PhD degree in Computer Science or a relevant technical field, with graduation expected by June 2026.
• Strong foundation in AI/ML, LLMs, Optimization, and related techniques.
• Experience with research, publishing, building, and scaling machine learning models using large datasets.
• An agile development mindset, valuing constant iteration and improvement.
• Ability to obtain and maintain work authorization in the country of employment (Canada) at the time of hire and throughout employment.

Preferred Qualifications

• Demonstrated proficiency in Python programming, with the ability to write clean, efficient, and well-documented code.
• Expertise in data management using Python libraries such as NumPy, Pandas, Matplotlib, and leveraging models from Hugging Face.
• Practical knowledge of applied machine learning and deep learning frameworks, like PyTorch.
• Exposure to Natural Language Processing (NLP), Computer Vision (CV), Reinforcement Learning (RL), and AI Optimization.
• Familiarity with state-of-the-art research in machine learning and AI, evidenced by relevant coursework, publications, or projects. Publications in top-tier AI conferences or journals are a significant asset.
• Excels in solving ambiguous and complex problems, navigating uncertainty, breaking down challenges, and developing innovative solutions.

Compensation and Benefits

Atlassian is committed to equitable and competitive compensation. For this AI Researcher role, the current base pay range for new hires in Zone A (Canada) is 130,500 CAD - 170,375 CAD. Compensation is determined by skills, expertise, and experience. This role may also include eligibility for benefits, bonuses, commissions, and equity. Further details on geographic pay zones and comprehensive perks and benefits can be found on Atlassian's career site.

Key skills/competency

• Machine Learning (ML)
• Artificial Intelligence (AI)
• Large Language Models (LLMs)
• Generative AI
• AI Optimization
• Python Programming
• PyTorch
• Natural Language Processing (NLP)
• Data Management
• Research & Experimentation