Senior Principal Machine Learning Engineer

Overview

Atlassian is looking for a Senior Principle Machine Learning Engineer to join us on our journey as we redefine productivity and collaboration in the digital age. As a Senior Principle Machine Learning Engineer you will be the driving force in integrating cutting-edge AI capabilities within Atlassian products. Your work will transform the way teams interact with our products like Jira and Confluence as we look to extract knowledge and insights from data to propel team work forward.

Your Role And Impact

• AI-Powered Atlassian Integration: Craft and implement innovative machine learning models in Atlassian tools. Imagine creating a smart Jira agent that can automatically categorize tickets based on content, or a Confluence assistant that summarizes documents and suggests related topics.
• Advanced Data Analysis: Dive deep into vast datasets to extract meaningful insights. Your work will power the AI models to understand complex user interactions and content within Atlassian tools to propel team work forward across the globe.
• Robust Model Development: Design, build, and refine models that can accurately perform tasks such as topic and entity extraction at scale. Picture a world where AI can automatically suggest experts within a team that can help move work forward.
• Collaborative Innovation: Join forces with product managers, designers, and developers. Your collaborative efforts will ensure that AI features are not only powerful but also intuitive and user-friendly.
• AI Evangelism: Be the voice of AI within the team. Educate and inspire your colleagues about the potential of AI, leading workshops and knowledge-sharing sessions.
  
  
  

Compensation

At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:

Zone A: $263,700 - $351,500

Zone B: $237,300 - 316,400

Zone C: $218,800 - 291,800

This role may also be eligible for benefits, bonuses, commissions, and equity.

Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.

Responsibilities

• Develop and implement machine learning algorithms to enhance our products
• Design and implement scalable data processing and machine learning pipelines
• Collaborate with product, engineering, and data teams to identify machine learning opportunities
• Evaluate and improve the performance of machine learning models
• Stay up-to-date with the latest developments in machine learning research and apply them to real-world problems
• Write clean, scalable, and maintainable code
• Communicate technical concepts and ideas to both technical and non-technical stakeholders
• Sharing your knowledge by giving brown bag sessions, tech talks, and evangelising appropriate tech and engineering best practices.
• Mentoring other team members, facilitating within/across team workshops, and leading agile development.
  
  
  

Qualifications

• Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience).
• 10+ years of industry experience in building production-grade machine learning systems with all aspects of research, model training, tuning, deploying, serving and monitoring.
• Be motivated, and self-driven in a fast (we truly mean fast) paced environment with a proven track record demonstrating impact across several teams and/or organisations.
• Ability to communicate and collaborate effectively with stakeholders and manage tasks in a timely manner.
• Ideas, opinions, and the ability to share them through respectful proposals, presentations, and team-wide discussions, An eagerness to work and learn in the open and share your learnings with your teammates.