Atlassian provides tools to help every team unleash their full potential.
The Role
Lead design and deployment of production-grade ML systems (ranking, retrieval, LLMs). Drive architecture decisions, run experiments and evaluations, build scalable feature pipelines and monitoring, mentor engineers, and collaborate cross-functionally to integrate AI into products and scale ML capabilities.
Summary Generated by Built In
Engineering | Mountain View, United States or Remote | Remote, Remote
As a Principal Machine Learning Engineer, you will drive the development and implementation of cutting-edge machine learning algorithms, training sophisticated models, and collaborating with product, engineering, and analytics teams to build AI functionalities into Atlassian products and services. Your daily responsibilities will encompass a broad spectrum of tasks - designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to emerging ML engineers. Your role is pivotal, ensuring AI's transformative potential is realized across our offerings.
Technical Leadership & Execution
Model Development & Experimentation
Cross-Functional Collaboration
Mentorship & Organizational Impact
Decision Making & Direction
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
As a Principal Machine Learning Engineer, you will drive the development and implementation of cutting-edge machine learning algorithms, training sophisticated models, and collaborating with product, engineering, and analytics teams to build AI functionalities into Atlassian products and services. Your daily responsibilities will encompass a broad spectrum of tasks - designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to emerging ML engineers. Your role is pivotal, ensuring AI's transformative potential is realized across our offerings.
Technical Leadership & Execution
- Drive complex decisions that impact the work of teams and change their technical direction over multiple quarters
- Regularly tackle the largest and most complex problems on the team, from technical design to launch
- Set the direction of systems and capabilities, balancing progress over perfection
- Determine plans-of-attack on large projects and solve complex architecture challenges
Model Development & Experimentation
- Design, develop, and deploy production-grade ML models (e.g., ranking, retrieval, LLM-based systems) to optimize user experience and achieve business objectives
- Conduct meticulous experimentation and model evaluations, backing decisions with data
- Develop robust feature engineering practices to ingest, process, and serve features for offline training and online inference at scale
- Oversee end-to-end deployment of ML solutions into production, ensuring continuous evaluation, monitoring, and improvement
Cross-Functional Collaboration
- Collaborate closely with product managers, designers, and engineering teams to integrate AI/ML capabilities into products
- Partner across engineering teams to take on company-wide programs spanning multiple projects
- Communicate complex technical concepts clearly to both technical and non-technical stakeholders
Mentorship & Organizational Impact
- Mentor and guide junior and senior engineers, fostering a culture of innovation, collaboration, and continuous learning
- Actively share knowledge and expertise through mentoring and coaching beyond direct reports
- Contribute to programs of work that scale across the department
- Identify, solve, and bridge gaps/problems across teams using experience and expertise
Decision Making & Direction
- Quickly collate and analyze key decision parameters, balancing speed, risk, and impact appropriately
- Limit ambiguity and risk by experimenting and prototyping
- Understand how contributions of multiple capabilities fit into larger products and platforms
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
Skills Required
- Design system and model architectures for large, complex ML systems
- Develop and deploy production-grade ML models (ranking, retrieval, LLM-based systems)
- Conduct rigorous experimentation and model evaluations to inform decisions
- Develop robust feature engineering practices for offline training and online inference at scale
- Oversee end-to-end deployment, continuous evaluation, monitoring, and improvement of ML solutions
- Drive complex technical decisions and set direction across teams and multi-quarter initiatives
- Mentor and coach junior and senior engineers and share expertise across the organization
- Collaborate with product, design, and engineering teams to integrate AI/ML into products
What the Team is Saying
Tiffany
Engineering Senior Associate, United States
Gautam
Software Engineer, United States
Tygrr
Product Manager, United States
Ashleigh
Frontend Engineer, United States
Jensen
Senior Frontend Software Engineer, United States
Javier
Senior Solutions Engineer, United States
Atlassian Compensation & Benefits Highlights
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Parental & Family Support — Parental leave spans 26 weeks for birthing parents and 20 weeks for non-birthing parents, alongside inclusive family-formation benefits such as fertility treatment, adoption, and surrogacy. Additional supports include menopause resources and caregiving-related programs.
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Retirement Support — Retirement programs include a U.S. 401(k) company match with immediate vesting and multiple contribution options. These are complemented by other financial wellbeing tools like HSAs/FSAs.
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Healthcare Strength — Medical coverage is paired with mental-health resources, disability and life insurance, and options such as HSA/FSA. Descriptions also point to solid plan choices with access to counseling, coaching, and 24/7 support.
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The Company
What We Do
Atlassian creates teamwork solutions for high-performing teams. Our portfolio of collaboration and work management software products includes Jira, Confluence, Trello, Loom and Rovo. More than 300,000 businesses worldwide rely on Atlassian’s technology, including 80 percent of Fortune 500 companies. Our solutions support various business teams and they help organizations plan, track, and deliver their biggest ideas together.
Why Work With Us
At Atlassian, we believe we can accomplish so much more together than apart — which is why everything from our tooling — to our distributed workforce — to how our teams are structured is rooted in collaboration. Come join us and help unleash the potential of every team.
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Employees work remotely.
Atlassians have flexibility in where they work to support their family, personal goals, and other priorities. Our approach to distributed work allows us to tap into talent beyond our office locations, and to reimagine how work gets done.
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