Lead the design and delivery of scalable machine learning systems and customer-facing generative AI applications for Rovo Chat. Build agent harnesses that improve quality, reliability, and latency; advance state-of-the-art AI capabilities; lead engineers through technical design and launch; and collaborate cross-functionally with teams and internal customers. The role also involves applying a deep understanding of the machine learning project lifecycle and supporting platform-based product development.
Engineering | San Francisco, United States | Remote, Remote | Full-Time
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 ML System Engineer in the Rovo & AI Engineering org, you will contribute to Atlassian's biggest bet and fastest area of growth, Rovo Chat. You will bring the latest bleeding edge innovations to the product and build agent harnesses that deliver a step function improvement in quality, reliability and latency.
You will have the opportunity to lead other engineers to drive involved projects from technical design to launch. You will also collaborate with other teams and internal customers to set expectations, gather input and communicate results. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across our offerings.
Your future team
The Rovo & AI Engineering org's mission is to make Rovo the fastest, most trusted way for any team to find, understand, and act on their organization's knowledge. Over the last year, the team has made rapid strides along this direction and the product surface has witnessed a 10x growth as a direct result of this effort.
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: $236,700 - $309,025
Zone B: $213,030 - $278,123
Zone C: $196,461 - $256,491
On your first day, we'll expect you to have
It would be great, but not required if you have
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: $236,700 - $309,025
Zone B: $213,000 - $278,123
Zone C: $196,400 - $256,491
This role may also be eligible for benefits, bonuses, commissions, and equity.
Please visit
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 ML System Engineer in the Rovo & AI Engineering org, you will contribute to Atlassian's biggest bet and fastest area of growth, Rovo Chat. You will bring the latest bleeding edge innovations to the product and build agent harnesses that deliver a step function improvement in quality, reliability and latency.
You will have the opportunity to lead other engineers to drive involved projects from technical design to launch. You will also collaborate with other teams and internal customers to set expectations, gather input and communicate results. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across our offerings.
Your future team
The Rovo & AI Engineering org's mission is to make Rovo the fastest, most trusted way for any team to find, understand, and act on their organization's knowledge. Over the last year, the team has made rapid strides along this direction and the product surface has witnessed a 10x growth as a direct result of this effort.
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: $236,700 - $309,025
Zone B: $213,030 - $278,123
Zone C: $196,461 - $256,491
On your first day, we'll expect you to have
- 7+ years of experience as a software developer
- Experience building customer facing Gen AI Applications at scale
- Experience pushing the state of the art to achieve breakthrough quality and reliability
- Deep understanding of Machine Learning projects lifecycle
- Experience leading and supporting senior engineers and working cross functionally
It would be great, but not required if you have
- Expertise in taking a platform approach to building product features, enabling multi team contributions
- Experience with efficiently scaling and deploying Machine Learning models
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: $236,700 - $309,025
Zone B: $213,000 - $278,123
Zone C: $196,400 - $256,491
This role may also be eligible for benefits, bonuses, commissions, and equity.
Please visit
Atlassian Boston, Massachusetts, USA Office
55 Causeway St, Boston, Massachusetts , United States, 02114
Atlassian Boston, Massachusetts, USA Office
Atlassian believes the future of work is distributed and offers our people the flexibility to help them do what’s important to them. And with few exceptions, we hire people anywhere we have a legal entity as long as they have eligible work rights and sufficient team time zone overlap.
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