Engineering | Sydney, Australia | Remote, Remote | Melbourne, Australia | Brisbane, Australia
Working at AtlassianAtlassians can choose where they workwhether 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.
Atlassian is seeking a Senior Machine Learning Engineer to join AI Context team within broader Rovo + AI organisation. You will help build the agentic LLM harnesses that power high-visibility Rovo AI features and enable contextually aware, intelligent experiences for every user and agent.
Your future teamYou will join AI Context, a team of software and machine learning engineers working across Sydney, Melbourne, Brisbane, and the US West Coast. The team has a mix of SWEs and MLEs and partners closely across Rovo + AI and product teams.
We build experiences around insights, modelling, and personalisation that help Atlassian products deliver relevant context to users and AI agents. We give engineers a high degree of ownership and autonomy, protect focus time through asynchronous collaboration, and use lightweight, ad hoc alignment when needed.
What you'll doAs a Senior Machine Learning Engineer, you will design, build, ship, and operate agentic LLM harness solutions for existing and new AI features. You will improve quality and reduce cost across production LLM systems, build robust evaluation capabilities, and contribute to areas such as fine-tuning and model serving.
You will help set the long-term technical direction for LLM harness engineering, incorporating rapid advances from the research community and industry. You will navigate complex systems, identify practical paths from current constraints to a durable architecture, and propose and execute improvements end to end.
You will act as a thought partner to Engineering Managers and Heads of Engineering, influence technical direction across stakeholder teams, and lead small virtual squads that own critical components. You will also coach junior engineers and help the team achieve its key results.
Your backgroundOn the first day, we'll expect you to have- Bachelor's or Master's degree, preferably in Computer Science or a related field, or equivalent practical experience
- 4+ years of related industry experience in machine learning, including hands-on experience designing, evaluating, and operating LLM-based or agentic systems
- Strong coding skills in Kotlin and/or Python, with the ability to write performant, production-quality code and work effectively with AI-assisted software development practices
- Experience building and operating machine learning systems in production, including the operational practices required to improve system quality, reliability, and cost
- Experience building datasets, evaluations, and benchmarks for systems operating at scale; familiarity with SQL, distributed data processing, and cloud data environments
- A strong ownership mindset and a track record of driving ambiguous technical outcomes from problem definition through delivery and operation
- Strong communication and influencing skills, with the ability to explain ML concepts to diverse audiences and steer technical direction with cross-functional stakeholders
- Experience leading technical work and coaching engineers in a collaborative team or virtual squad
- A pragmatic, iterative approach that balances a high bar for quality with the value of delivering, learning, and improving
It's great, but not required, if you have- Experience fine-tuning smaller language models
- Experience serving and operating LLMs using technologies such as NVIDIA Triton Inference Server
- Experience applying machine learning to personalisation or context-aware product experiences
- Experience solving complex problems in enterprise SaaS or similarly large-scale product environments
Benefits & PerksAtlassian 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
