Senior Machine Learning System Engineer

Senior Machine Learning System EngineerAs 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 EngineeringDesign 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 & ServingBuild 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 & RetrievalDesign 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 DisciplineDrive 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 CollaborationWork 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.