Working at Atlassian 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. As a senior Machine Learning Systems Engineer on the Search Platform team, you will own and drive the design, development, and production deployment of machine learning systems that power search experiences across Atlassian's product suite, including Jira, Confluence, and Rovo. Search Platform Engineering 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 that meet strict SLO targets for availability, latency, and relevance quality. ML Model Development & Serving Build and maintain production ML models including neural rankers, embedding models, and reranking systems. Integrate models into serving infrastructure using frameworks such as Triton and PyTorch, ensuring reliability, scalability, and cost efficiency. Collaborate with ML researchers to translate experimental models into production-grade systems with robust monitoring and evaluation harnesses. Agentic Search & Retrieval Design retrieval systems purpose-built for agentic and RAG (Retrieval-Augmented Generation) use cases, including personalized indexes, grounding pipelines, and multi-step retrieval workflows. Partner with Rovo and AI platform teams to evolve search infrastructure as a foundational layer for AI agents, ensuring retrieval quality, freshness, and relevance at scale. Operational Excellence & Cost Discipline Drive observability, monitoring, and incident response for search serving systems. Apply FinOps principles to identify and execute cost optimization opportunities across vector search infrastructure and ML serving fleets. Maintain production health through rigorous on-call practices, runbook development, and proactive capacity planning. Cross-Functional Collaboration Work closely with engineering leads, product managers, and platform stakeholders to define technical roadmaps and deliver against team OKRs. Mentor junior engineers, contribute to design reviews, and champion engineering best practices across the team. Benefits Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits . About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh . In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.
