Work setup in the employer’s posting: TELECOMMUTEFrom the employer’s posting
Design and build knowledge-grounded LLMs, embeddings and multimodal models
Fine-tune and adapt foundation models to Atlassian's data using retrieval-augmented strategies
Run POC experiments on agentic workflows and GenAI-powered assistants
Define evaluation methods for groundedness and hallucination detection
Mentor engineers and scientists as technical anchor of a small tiger team
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.
Drive POC experimentation, from agentic workflows to novel GenAI-powered assistants.
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, mentoring engineers and scientists.
6+ years in ML/AI engineering, with deep expertise in LLMs, NLP, or search.
Experience with multimodal models, knowledge graphs, or semantic embeddings.
Hands-on experience with retrieval-augmented generation (RAG), embeddings, hybrid retrieval, or agentic workflows.
Familiarity with evaluation metrics for search/GenAI (NDCG, groundedness, human preference modeling).
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.
📚 Education - Master’s or PhD in Computer Science, Machine Learning, or related field preferred—or equivalent industry experience. Nice to Have
From the employer’s posting.
At Atlassian, we're motivated by a common goal: to unleash the potential of every team.
In the employer’s words · Read in context
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 65
Similar jobs usually come down between day 6 and day 70.
Well past Atlassian’s usual: its jobs come down by about day 25.
From 4,581 similar postings that came down, and 26 of Atlassian’s. Coming down is not always a hire.
49 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume to compare the role’s scope, tools and requirements with your experience.
Complete your application on careers-apac-atlassian.icims.com. The employer’s form will show what is required.
Already applied? Track this application
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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 Principal Machine Learning Engineer (P60) to join our new GenAI Products & Innovation Forge in Singapore. This is a hands-on technical leadership role where you’ll push the boundaries of advanced GenAI Products with enterprise knowledge, rapid prototyping, and applied research—turning state-of-the-art techniques into high-impact innovations across Atlassian.
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.
🧠 Advance GenAI Products 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.
⚡ Prototype & Experiment Rapidly
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.
🤝 Provide Technical Leadership
Act as the technical anchor of a small tiger team, 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.
🚀 Shape Innovation Strategy
Contribute to the roadmap for the Forge as a global hub for advanced GenAI products 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.
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.
This role may also be eligible for benefits, bonuses, commissions, and equity.
✅ Experience
6+ years in ML/AI engineering, 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.
💡 Skills
Expert-level knowledge of GenAI ecosystems (OpenAI, Anthropic, Mistral, OSS) and fine-tuning/serving frameworks.
Deep technical skills across modeling, infrastructure, and orchestration (LangChain, LlamaIndex, vector DBs).
Strong prototyping ability, balancing speed with rigor in experimentation.
Ability to set technical direction and inspire peers with thought leadership.
📚 Education
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.
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.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
01
- 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.
No clear work-authorization passage found. Eligibility is unconfirmed.