Principal ML Engineer — Remote AI at Scale

Atlassian; New York (NY); Hybrid; USD 213,000 - 309,000; Full time

Job summary

Atlassian is seeking a Principal Machine Learning Engineer for the Confluence AI team. You will shape AI-powered experiences, lead end-to-end ML system design, and drive production-grade capabilities at scale.

You will collaborate across product, platform, and partner teams to set direction, evaluate models, and ensure reliable delivery of AI features while balancing performance, cost, and safety.

Responsibilities

• Set technical direction for ML/AI initiatives powering Confluence experiences (content creation, editing, summarization, recommendations, multimodal interaction).
• Design, build, and evolve production-grade ML systems, evaluation workflows, experimentation loops, and supporting infra for scalable AI features.
• Lead development of customer-facing AI capabilities by turning opportunities into concrete technical strategies, measurable outcomes, and shipped experiences.
• Advance model behavior, retrieval, ranking, prompt and workflow design, automated evaluation, quality measurement, and system reliability.
• Collaborate with engineering, product, design, analytics, and platform teams to align priorities, influence roadmaps, and drive cross-organizational initiatives.
• Identify systemic failure modes, implement interventions, and close loop between improvements and customer impact via experimentation.
• Make architectural decisions balancing model quality, latency, cost, safety, maintainability, and user experience.
• Contribute hands-on when needed—prototyping, implementation, debugging, and guiding complex production rollouts.
• Mentor engineers, lead design reviews, raise technical quality, and establish reusable patterns across teams.
• Build foundations for deeper, more integrated Confluence AI experiences across editor surfaces and content types.

Job description

Atlassian is seeking a Principal Machine Learning Engineer for the Confluence AI team. You will shape AI-powered experiences, lead end-to-end ML system design, and drive production-grade capabilities at scale.

You will collaborate across product, platform, and partner teams to set direction, evaluate models, and ensure reliable delivery of AI features while balancing performance, cost, and safety.