Head of Engineering

Atlassian is a global leader in team collaboration and productivity software, empowering teams to unleash their potential and achieve remarkable results. Our suite of tools, including Jira, Confluence, Trello, Bitbucket, and Rovo, is trusted by millions of users worldwide to plan, track, and manage their work effectively. At Atlassian, we are dedicated to building innovative tools and technologies that drive the future of work.

We are looking for a Principal Machine Learning Engineer to become a part of our Rovo & AI organization. This team is responsible for creating Atlassian's leading AI products, essential infrastructures, data pipelines, frameworks, models, and other capabilities that accelerate AI feature development across the entire company.

What you'll do

As a Principal Machine Learning Engineer, you will drive the development and implementation of the cutting edge machine learning algorithms, training sophisticated models, collaborating with product, engineering, and analytics teams, to build the AI functionalities into each Atlassian products and services. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to emerging ML engineers. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across our offerings.

• Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience)
• 5+ years of related industry experience in the data science domain
• Expertise in Python or Java with the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)
• Experience building and scaling machine learning models in business applications using large amounts of data
• Ability to communicate and explain data science concepts to diverse audiences, craft a compelling story
• Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future"
• Agile development mindset, appreciating the benefit of constant iteration and improvement

• Experience with continued pre-training, fine-tuning, and optimizing state-of-the-art text and multimodal embedding models, information retrieval models, and/or LLMs
• Experience developing deep learning-based models and LLM-related applications, especially agentic workflows and multi-step reasoning systems
• Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
• Excelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions.