Principal Machine Learning Engineer

Working at Atlassian

Atlassians can choose where they work whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.

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.

On the first day, we'll expect you to have

• 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 and 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 working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
• Experience in developing deep learning-based models and working on LLM-related applications
• 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