ApplySarthi

Principal Machine Learning Engineer

Atlassian

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1,109 open learning roles across 230 companies are on ApplySarthi right now, most of them in Bengaluru (63), Hyderabad (25), Delhi NCR (14).

What learning roles keep asking for: Machine learning (49%), Python (36%), LLMs (23%), PyTorch (23%), Deep learning (16%), AWS (13%), Generative AI (13%) — counted across their open postings here.

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Atlassian has 276 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

Preparing for this interview

Interviews for learning roles keep coming back to Machine learning, Python, LLMs, PyTorch. Practise those questions before you sit with Atlassian.

Questions you are likely to be asked

  1. Why do you want to join Atlassian?
  2. What is your experience with Confluence? Tell me one thing you learned the hard way.
  3. Tell me about a time the data was messy or wrong. What did you do?
  4. How would you explain your model's result to someone who is not technical?
  5. What would you check first if a model's accuracy dropped after going live?

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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. As a Principal Machine Learning Engineer in the Confluence AI organization, you will help shape the next generation of AI-powered experiences across Confluence. This is a hands-on principal-level role for an engineer who can turn fast-moving advances in machine learning into high-quality product experiences that reach customers at scale. You will work across product, platform, and partner teams to define technical direction, solve ambiguous problems, and deliver AI capabilities that improve how users create, edit, discover, and interact with content. The role spans the full stack of AI product development, from model-informed product design and evaluation strategy to production engineering, experimentation, and long-term technical leadership. This role is especially well suited for someone who combines strong machine learning depth with product instinct and systems thinking. Success in this position means not only building sophisticated AI systems, but also identifying the highest-value opportunities, raising engineering standards, and helping multiple teams move faster and with more confidence. Set technical direction for machine learning and AI initiatives that power Confluence experiences across areas such as content creation, editing, summarization, recommendations, and multimodal interaction. Design, build, and evolve production-grade ML systems, evaluation workflows, experimentation loops, and supporting infrastructure that enable reliable delivery of AI features at scale. Lead the development of customer-facing AI capabilities by translating ambiguous product opportunities into practical technical strategies, measurable outcomes, and shipped experiences. Drive advances in areas such as model behavior, retrieval, ranking, prompt and workflow design, automated evaluation, quality measurement, and system reliability. Partner closely with engineering, product, design, analytics, and platform teams to align on priorities, influence roadmaps, and deliver cross-organizational initiatives. Identify systemic product or model failure modes, develop interventions, and close the loop between technical improvements and customer impact through experimentation and data-driven iteration. Make high-leverage architectural decisions across application layers, balancing model quality, latency, cost, safety, maintainability, and user experience. Contribute as a deeply hands-on engineer when needed, including prototyping, implementation, debugging, and guiding complex production rollouts. Raise the bar for principal-level engineering by mentoring other engineers, leading design reviews, improving technical quality, and establishing reusable patterns that benefit multiple teams. Help build the foundations that allow Confluence AI teams to ship deeper, more integrated AI experiences across editor surfaces, content types, and collaborative workflows. 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. In The United States or Remote , we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are: Zone A : $236,700 - $309,025 Zone B : $213,030 - $278,123 Zone C : $196,461 - $256,491

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