Job description

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. Your future team Atlassian is betting that the next era of teamwork will be shaped by people and AI agents working together, with Rovo as the intelligent teammate that understands an organization’s context and helps move work forward. Turning Rovo’s reach into lasting customer value, experiences people trust, return to, and rely on, is central to Atlassian’s ambition to lead in AI and to our next chapter of growth. Getting quality right is what turns that ambition into customer success, deeper adoption, and durable business impact. You’ll join the Rovo Chat Quality team within Atlassian’s Rovo + AI organization. We are the team that turns “make Rovo better” into something we can measure, understand, and ship. We build the evaluation systems, datasets, quality signals, and production ML capabilities that reveal where Rovo succeeds, where it falls short, and which changes make it meaningfully more useful to customers. What you’ll do As a Senior 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. • 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. Your background We expect you to bring: • 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. • 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 & Perks Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits . About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh . In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes. 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. Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. This role may also be eligible for benefits, bonuses, commissions, and equity.

Requirements

Must-haves

Working at Atlassian
Your future team
What you’ll do
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.
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.
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.

Nice-to-haves

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Keywords to mirror

aimlmachine learningllmgo

Platform: atlassian
Effort: medium

Benefits

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