Principal Machine Learning Engineer

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.

At Atlassian, we’re on a mission to unleash the potential of every team. As part of that mission, we're investing deeply in Generative AI — pioneering advanced modeling and rapid innovations that accelerate how teams work, discover, and create.

We’re seeking a new Principal Machine Learning Engineer (P60) to join our new GenAI Modeling & Jira Search team. This is a hands‑on technical leadership role where you’ll push the boundaries of advanced GenAI modeling, rapid prototyping, and applied research—turning state‑of‑the‑art techniques into high‑impact innovations across Atlassian.

Design and build novel approaches for knowledge-grounded LLMs, embeddings, and multimodal modeling.

Explore fine‑tuning, post‑training, and retrieval‑augmented strategies to adapt foundation models to Atlassian’s data.

Lead technical explorations that expand the frontier of what’s possible in applied generative modeling.

Drive POC experimentation, from agentic workflows to novel GenAI‑powered assistants.

Translate research ideas into fast, working prototypes that demonstrate user value.

Define and implement evaluation methods (groundedness, hallucination detection, human‑in‑the‑loop) to measure success.

Act as the technical anchor of a small tiger team (manager + ICs), mentoring engineers and scientists.

Influence design and implementation across retrievers, rankers, orchestration, and serving infrastructure.

Collaborate with product and platform teams to transition prototypes into scalable systems.

Contribute to the roadmap for the Forge as a global hub for advanced GenAI modeling and applied research.

Partner with peers across Rovo, Jira Search, Knowledge AI, and Platform to drive cross‑team impact.

Champion responsible AI, groundedness, and data quality in all innovations.

Extensive experience in ML/AI engineering (generally 6+ years), with deep expertise in LLMs, NLP, or search.

Proven track record of building and shipping ML‑powered or GenAI‑integrated products.

Hands‑on experience with retrieval‑augmented generation (RAG), embeddings, hybrid retrieval, or agentic workflows.

Strong background in scaling ML systems from prototype to production.

Expert‑level knowledge of GenAI ecosystems (OpenAI, Anthropic, Mistral, OSS) and fine‑tuning/serving frameworks.

Deep technical skills across modeling, infrastructure, and orchestration (Lang Chain, Llama Index, vector DBs).

Strong prototyping ability, balancing speed with rigor in experimentation.

Ability to set technical direction and inspire peers with thought leadership.

Master’s or PhD in Computer Science, Machine Learning, or related field preferred—or equivalent industry experience.

Experience with multimodal models, knowledge graphs, or semantic embeddings.

Familiarity with evaluation metrics for search/GenAI (NDCG, groundedness, human preference modeling).

Contributions to open‑source ML frameworks or GenAI research communities.

Passion for mentoring, fostering innovation, and shaping a new AI hub in Singapore.

At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. In the United States, we have three geographic pay zones.

For this role, our current base pay ranges for new hires in each zone are:

Zone A: $232,200 - $303,150

Zone B: $209,700 - $273,775

Zone C: $193,500 - $252,625

This role may also be eligible for benefits, bonuses, commissions, and equity.

Please visit  for more information on which locations are included in each of our geographic…