Principal Machine Learning Engineer

Atlassian•Seattle, WA

4d•$196,461 - $309,025•Hybrid

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. As a Principal ML Engineer in the Rovo & AI Engineering org, you will contribute to Atlassian’s biggest bet and fastest area of growth, Rovo Chat. You will bring the latest bleeding edge innovations to the product and build agent harnesses that deliver a step function improvement in quality, reliability and latency. You will have the opportunity to lead other 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. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across our offerings. What you’ll do As a Principal Machine Learning Engineer, you’ll tackle the open-ended technical problems that determine whether customers trust Rovo with increasingly complex and consequential work. You’ll remain deeply hands-on while setting direction across teams: driving advances in models, agents, and evaluation and turning them into measurable improvements for millions of active users. 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.

Requirements

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.
7+ years of experience as a software developer
Experience building customer facing Gen AI Applications at scale
Experience pushing the state of the art to achieve breakthrough quality and reliability
Deep understanding of Machine Learning projects lifecycle
Experience leading and supporting senior engineers and working cross functionally

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.