Principal Machine Learning System Engineer
Seattle - United States - Seattle, Washington United States; Remote - Remote; San Francisco - United States - San Francisco, California 94104 United States
Overview
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.
Responsibilities
As a Principal Machine Learning Systems Engineer, you will lead the design, development, and deployment of scalable machine learning (ML) systems and infrastructure. You will collaborate closely with data scientists, software engineers, and product teams to translate complex ML models into production-ready solutions. Your responsibilities include optimizing model performance, ensuring system reliability, and implementing efficient data pipelines. You will drive architectural decisions for high-performance computing and cloud-based ML platforms, ensuring scalability and security. Additionally, you will mentor junior engineers, promote best practices in ML operations (MLOps), and stay updated on emerging technologies to guide strategic innovation. Your role is critical in delivering robust, scalable, and efficient machine learning solutions that support business growth and innovation.
Qualifications
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $229,200 - $305,600
Zone B: $206,300 - $275,100
Zone C: $190,300 - $253,700
This role may also be eligible for benefits, bonuses, commissions, and equity.
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.
Our perks & benefits
Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit go.atlassian.com/perksandbenefits to learn more.
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.
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Bonuses Commissions Competitive compensation Equity Equity opportunities Health coverage Paid volunteer days Remote-first company Variety of perks Wellness resources
Tasks- Collaboration
- Deploy scalable solutions
- Design ML systems
- Development
- Develop ML infrastructure
- Drive architectural decisions
- Innovation
- Mentor junior engineers
- Optimize model performance
Atlassian Best Practices C Cloud Cloud-based platforms Collaboration Data Pipelines Design Go Health Coverage High Performance Computing Innovation Learning Legal Machine Learning Mentoring ML Ml operations ML Systems Onboarding Operations Optimization Performance Product Reliability Scalability Security Software Software Products System reliability Team Collaboration Wellness Resources
Education TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9