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Atlassian

Principal Machine Learning Engineer

Sorry, this job was removed at 02:07 a.m. (IST) on Sunday, Feb 01, 2026
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In-Office or Remote
Hiring Remotely in Bengaluru, Bengaluru Urban, Karnataka
In-Office or Remote
Hiring Remotely in Bengaluru, Bengaluru Urban, Karnataka

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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. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
  • Regularly tackle the largest and most complex problems in the team, from technical design to launch.
  • Work closely with Product, Engineering and Design leads in Jira AI, and translate their requirements into solid engineering deliverables, delegating work to the teams.
  • Deliver solutions that are used by other teams and products.
  • Follow a Product Engineer mindset by building features that are data-driven and customer-centric, fostering that culture within the Jira AI group.
  • Exceptional problem solving ability using ML, AI and core software engineering.Routinely tackle complex architecture challenges and define architectural standards.
  • Actively contribute to the code delivery through leading code reviews & documentation, direct contribution and fixing complex bugs in high-risk surface areas.
  • Expertise in data analysis, statistical methods, and logical reasoning to inform data-driven decision-making.
  • Partner across engineering teams to take on company-wide initiatives spanning multiple projects.
  • Mentor junior members on the team.

On your first day, we'll expect you to have:
  • Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin and Python).
  • Understanding of Machine Learning project lifecycle/tools along with prompt engineering.
  • Experience in architecting and implementing high-performance RESTful microservices.
  • Experience building and operating large scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking).
  • Experience with leveraging LLMs effectively and optimizing model usage on GPUs.
  • Experience with Databricks or Apache Spark.
  • Experience with Continuous Delivery and Continuous Integration.

It would be great, but not required:
  • Expert-level SQL knowledge, query tuning, schema design, and ETL processes.
  • Experience with Amazon Sagemaker.
  • Experience with scaling and deploying Machine Learning models.

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