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Principal Machine Learning Engineer

Atlassian · Remoto Brasil · Flexible / Remote

Publicada em 28/08/2026

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Working at AtlassianAtlassians 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.As a Principal ML Engineer in the Rovo & AI Engineering org, you will contribute to Atlassian's biggest bet and fastest area of growth, Rovo Chat. You will bring the latest bleeding edge innovations to the product and build agent harnesses that deliver a step function improvement in quality, reliability and latency.You will have the opportunity to lead other engineers to drive involved projects from technical design to launch. You will also collaborate with other teams and internal customers to set expectations, gather input and communicate results. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across our offerings.What you'll doAs a Principal Machine Learning Engineer, you'll tackle the open-ended technical problems that determine whether customers trust Rovo with increasingly complex and consequential work. You'll remain deeply hands-on while setting direction across teams: driving advances in models, agents, and evaluation and turning them into measurable improvements for millions of active users.Set the technical vision for how Atlassian measures and improves Rovo Chat, translating qualities such as helpfulness, correctness, judgment, and reliability into rigorous evaluation strategies.Architect and build production ML and evaluation systems that operate at scale, including datasets, simulations, automated judges, regression suites, experimentation platforms, and online quality signals.Advance the state of Rovo's agentic capabilities across reasoning, planning, tool selection and use, action correctness, retrieval, memory, and long-horizon execution.Close the loop between evaluation and product impact: identify syst
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