Machine Learning Systems Engineer

Atlassian • San Francisco, CA

12d • Remote

About The Position

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. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. About Central AI Org Our organisation is designed to accelerate AI innovation across all our products and platform, provide cohesive AI experiences and setup up an Atlassian AI infrastructure for the future. Our purpose is to: Build horizontal AI capabilities and infrastructure which provides leverage across products Build a centralised Search, Q&A and Conversational AI across all Atlassian products. Explore integration of Atlassian products with AI products outside Atlassian. About AI & ML Platform Team Our team is building the foundations to democratise Machine Learning for Atlassian's teams, customers and ecosystem. Our goal is to create tools that are user-friendly and reliable, ensuring that Atlassian teams can easily embrace and utilize them. These tools will facilitate the development, deployment, measurement, and operation of AI & ML experiences. They will seamlessly integrate with the Atlassian Data Platform, enabling teams to efficiently and rapidly incorporate AI & ML capabilities into their workflows. The focus is on providing a smooth and hassle-free experience for Atlassian users, allowing them to leverage the power of AI & ML without any complications.

Requirements

• Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin).
• Understanding and experience with Machine Learning project lifecycle and tools.
• Understanding of LLMs, best deployment practices and inference optimisation.
• Experience in building and implementing high-performance RESTful micro-services.
• Experience building and operating large scale distributed systems using Amazon Web Services (Sagemaker, S3, Cloud Formation, AWS Security and Networking).
• Experience with Continuous Delivery and Continuous Integration.

Responsibilities

• As a Machine Learning Systems Engineer on the AI & ML Platform team, you will build and scale the core infrastructure to allow software engineers, ML engineers & data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines.
• Along with that, you will build systems for product teams like Jira & Confluence to provide access to curated LLMs.
• You will use your software development expertise to solve difficult problems, tackling infrastructure and architecture challenges.
• You will have the opportunity to lead engineers to drive involved projects from technical design to launch.
• You will also collaborate with other teams and internal customers to set expectations, gather input and communicate results.
• Regularly tackle complex problems in the team, from technical design to launch.
• Routinely tackle complex architecture challenges and defines coding standards & patterns for the team.
• Lead the team through times of ambiguity, help them adapt and and deliver positive impact.
• Mentor junior members on the team.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees