Senior Machine Learning System Engineer

About the role

Atlassian is hiring a Senior Machine Learning System Engineer on its Search Platform team. You will own and drive the design, development and production deployment of machine learning systems that power search across Atlassian's product suite, including Jira, Confluence and Rovo. The role is open to remote work and to offices in Seattle, San Francisco, Austin and New York.

Key responsibilities

• Design and implement scalable search serving infrastructure, including retrieval pipelines, vector indexing systems and embedding-based semantic search.
• Own end-to-end delivery of ML components from experimentation through production rollout across multiple regions and tenants.
• Contribute to the architecture of high-throughput, low-latency search systems meeting strict SLO targets for availability, latency and relevance quality.
• Build and maintain production ML models such as neural rankers, embedding models and reranking systems, integrating them with frameworks such as Triton and PyTorch.
• Collaborate with ML researchers to turn experimental models into production systems with monitoring and evaluation.
• Design retrieval systems for agentic and RAG use cases, including personalized indexes, grounding pipelines and multi-step retrieval workflows, working with Rovo and AI platform teams.
• Drive observability, monitoring and incident response, apply FinOps principles to optimize costs, and maintain production health through on-call practices, runbooks and capacity planning.
• Work with engineering leads, product managers and platform stakeholders on technical roadmaps and team OKRs, mentor junior engineers and take part in design reviews.

What we offer

• Base pay for new hires depending on location: Zone A $180,000-$235,000, Zone B $162,000-$211,500, Zone C $149,400-$195,050.
• Possible eligibility for benefits, bonuses, commissions and equity.
• Health and wellbeing resources and paid volunteer days among other perks.