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We are looking for a Principle ML engineer to join the Teamwork Graph team and a group of talented engineers who are responsible for helping build and deploy the knowledge graph of how teams work together. The graph is the foundational data layer Teamwork Graph logically representing all of a customer’s data, with edges/relationships to connect entities across feature and product boundaries. The Graph powers various new AI products such as Rovo, as well as enables Atlassian products to work better together. You will work closely with the team to execute the strategy for advanced graph querying and powering a suite of Graph + AI powered applications and experiences. You will also collaborate with the federated product teams and other central orgs to integrate the Teamwork knowledge deeply in various products such as Search, Jira, Confluence, and many upcoming ones.
Job Responsibility:
Process and structure large amounts of graph data to power applications across Atlassian
Build great APIs
Creative use of generative AI and ML to process, structure, and reason over large amounts of data to power intelligent products
Mentor and coach your team members on best practices, code quality, design patterns, testing, debugging, and documentation
Communicate effectively with internal and external partners, present technical concepts and results clearly and concisely, and solicit feedback and input from various stakeholders
Requirements:
10+ years of experience building and scaling business applications and systems using large amounts of data
Built generalizable platforms with a keen eye on empowering applications in product
Agile development mindset, appreciating the benefit of iteration and improvement
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