Principal Machine Learning Engineer

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. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.

As a Principal Machine Learning Engineer, you will set the technical direction for how AI is built and shipped across Jira Service Management (JSM) - one of Atlassian's largest and most varied enterprise surfaces. You'll design and continuously improve the multi-step LLM pipelines that power our AI service experiences: shaping prompting strategies, model selection, output parsing, and orchestration to raise quality and reliability across a wide range of real-world service scenarios. Your work will go deep on the problems that separate impressive demos from dependable enterprise products. You'll build retrieval and grounding systems that surface the right context at the right moment - knowledge articles, past requests, structured data, and tool outputs - so that AI makes decisions grounded in relevant, trustworthy information. You'll own the quality, latency, cost, and reliability of AI workflows running at enterprise scale across a large and diverse customer base, and you'll make quality measurable: designing evaluation frameworks, benchmark datasets, and scoring methods that give teams a credible, stable signal on whether AI is genuinely improving or quietly regressing. Equally, you'll bring rigor to how we learn. You'll run disciplined experiments that validate whether changes to models, prompts, or retrieval actually move the needle - and build the infrastructure to run those experiments repeatedly and confidently. As a Principal, your influence stretches well beyond your own code: you'll set multi-quarter ML strategy, make architectural decisions that span multiple teams, mentor and grow emerging ML engineers, and raise the overall bar for how AI is built and shipped across JSM. This is a role for someone who wants their fingerprints on both the deepest technical decisions and the long-term trajectory of AI in a product used by teams worldwide.

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