Principal Machine Learning System Engineer

Working at Atlassian

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As a Principal Machine Learning Systems Engineer on the Search Platform team, you set the technical direction for search infrastructure that powers Rovo, Jira, Confluence, and the broader Atlassian AI platform. You operate with broad organizational influence, driving outcomes across teams and functions without relying on positional authority.

Technical Vision & Cross-Team Leadership
Define and champion the multi-year technical roadmap for search serving, vector infrastructure, and agentic retrieval. Identify architectural inflection points such as the evolution from keyword to semantic search, or the shift toward retrieval-for-agents and build organizational consensus around the right path forward. You earn alignment through technical credibility, clear reasoning, and the ability to make complex tradeoffs legible to engineers, product managers, and senior leadership alike.

Leading Without Authority
Drive high-impact initiatives across teams that do not report to you. Influence peers, partner teams, and stakeholders by framing problems compellingly, co-authoring shared technical strategies, and creating forums deep dives, design reviews, working groups where the best ideas win on merit. Navigate ambiguity and competing priorities across the Search Platform, ML Platform, AI Gateway, and Rovo product teams to keep critical cross-functional programs on track.

Agentic Search & Retrieval Architecture
Own the technical strategy for retrieval systems that ground Rovo agents and AI workflows, including personalized indexes, multi-step retrieval pipelines, and RAG infrastructure at scale. Anticipate how agentic use cases will stress existing search architecture and proactively design for those requirements before they become blockers.

Platform Scalability & Operational Excellence
Set the standard for production ML serving, cost discipline, and reliability across the search stack. Drive FinOps-oriented decisions such as vector cluster right-sizing and query embedding caching that deliver material infrastructure savings without sacrificing SLO targets.

Engineering Craft & Mentorship
Raise the technical bar across the organization through code review, design feedback, and sponsoring the growth of senior engineers toward principal-level impact.

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