Senior Machine Learning Systems Engineer

As a Senior Machine Learning System Engineer on the AI & ML Platform team, you will play a pivotal role in developing and refining the core infrastructure that empowers all Atlassian software engineers, ML engineers, and data scientists to create, train, evaluate, deploy, and manage Machine Learning models and pipelines.

You will collaborate closely with product teams, such as Jira and Confluence, to solve their specific challenges in building ML solutions. This may involve curating high-quality ML datasets, fine-tuning open-sourced Large Language Models (LLMs), or accessing proprietary LLMs. Your expertise in both ML and software development will be instrumental in overcoming challenging problems and navigating complex infrastructure and architectural issues.

This position offers you the chance to lead projects from the technical design phase all the way to launch. You will partner with various teams and internal stakeholders to achieve impactful results.

* Collaborate with your teammates to solve complex problems, from technical design to launch.

* Deliver cutting-edge solutions that are used by other Atlassian teams and products to build AI features that reach millions of customers.

* Deliver code reviews, documentation & bug fixes within a strong engineering culture

* Partner across engineering teams to take on company-wide initiatives spanning multiple projects.

* Mentor junior members of the team.

At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.

This role may also be eligible for benefits, bonuses, commissions, and equity.

* 6+ years of general software engineering experience with 2+ years in building Machine Learning and AI infra/Platform/Systems

* Comprehensive ML lifecycle expertise: Proven experience developing, deploying, and maintaining end-to-end ML systems, from data engineering to model serving and monitoring.

* Large-scale system design: Extensive experience designing and building scalable, fault-tolerant, and high-performance distributed systems for machine learning.