[Remote] Principle Machine Learning Systems Engineer

Note: The job is a remote job and is open to candidates in USA. Atlassian is hiring a Principal Machine Learning Systems Engineer for its Rovo Chat Quality team. The role sets technical direction and builds production machine learning and evaluation systems to improve Rovo Chat’s quality, agent capabilities, and customer outcomes.

Responsibilities

• Set the technical vision for how Atlassian measures and improves Rovo Chat, translating qualities such as helpfulness, correctness, judgment, and reliability into rigorous evaluation strategies
• Architect and build production ML and evaluation systems that operate at scale, including datasets, simulations, automated judges, regression suites, experimentation platforms, and online quality signals
• Advance the state of Rovo’s agentic capabilities across reasoning, planning, tool selection and use, action correctness, retrieval, memory, and long-horizon execution
• Close the loop between evaluation and product impact: identify systemic failure modes, develop interventions, ship them to production, and establish whether they improved customer outcomes
• Make high-leverage technical decisions across model choice, prompting, fine-tuning, data strategy, system architecture, and inference; balancing quality with latency, reliability, safety, and cost
• Lead ambitious, cross-organizational initiatives with ML, engineering, product, analytics, research, and design partners, creating clarity and momentum where neither the problem nor the solution is well defined
• Establish reusable methods, systems, and quality standards that raise the bar not only for Rovo Chat, but for AI-powered experiences across Atlassian
• Multiply the impact of other engineers through technical leadership, design reviews, mentorship, and a compelling long-term vision for how we build and evaluate world-class AI products

Skills

• A track record of architecting and shipping large-scale ML or AI systems that deliver measurable customer and business impact
• Deep experience with LLM-powered products, agentic systems, model evaluation, experimentation, and dataset development
• Strong production engineering skills and the ability to remain hands-on in a modern ML stack
• Principal-level technical leadership: setting direction, influencing across teams, and leading complex initiatives from ambiguity to production
• Excellent product and technical judgment, including balancing quality, speed, reliability, safety, latency, and cost
• The ability to communicate complex ideas clearly and raise the effectiveness of engineers around you through mentorship and technical leadership

Benefits

• Atlassians can choose where they work – whether in an office, from home, or a combination of the two.
• Health and wellbeing resources
• Paid volunteer days
• This role may also be eligible for benefits, bonuses, commissions, and equity.

Company Overview

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