Working at Atlassian

Atlassian can hire people in any country where we have a legal entity. Assuming you have eligible working rights and a sufficient time zone overlap with your team, you can choose to work remotely or return to an office as they reopen (unless it’s necessary for your role to be performed in the office). Interviews and onboarding are conducted virtually, a part of being a distributed-first company.

Atlassian is looking for a Machine Learning Scientist who is interested in improving the way that teams collaborate on Trello. You will be one of the pioneering ML experts in this area, and will shape the future of machine learning in Trello for years to come. You will work with product managers, designers, and other data scientists in Trello and the larger Atlassian company.

Your future team

The Core Machine Learning team at Atlassian is a centralized group of machine learning scientists and engineers. We partner with teams across Marketing, Growth, and Product to pursue machine learning applications that create revenue or product enhancements. We practice a remote-friendly work style, and we have team members located across multiple cities in both the US and Australia.

What you'll do

• Translate product and customer requirements into a feature roadmap
• Explore ML applications and ideas for content recommendation, personalization, and insight generation
• Build ML pipelines, models, and jobs at scale
• Share vision and roadmap with partners in product, design, engineering, and data science

Your background

• We'll expect you to have
• Bachelor or higher degree in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience)
• 2 or more years of industry or academic experience in the data science or machine learning domain
• Expertise in Python, SQL, or Spark and a working knowledge of version control tools (e.g. Git, Bitbucket)
• Explain data science and machine learning concepts to diverse audiences and create a compelling story
• Familiarity with deploying and monitoring machine learning models
• A curiosity to master new product domains
• It's Great, But Not Required, If You Have
• Previous experience in a product-focused ML role
• Experience with the following (Airflow, Databricks, Sagemaker, and Tensorflow / PyTorch)