Principal Machine Learning Engineer
Listed on 2026-01-12
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer
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OverviewAtlassians 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.
ResponsibilitiesAdvance GenAI Modeling with Knowledge
- 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. … (details omitted for brevity) …
About AtlassianAt Atlassian, we’re motivated by a common goal: to unleash the potential of every team. ...
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.
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