Lead ML Systems Engineer, GenAI Platform

Atlassian Corp.; United States; Hybrid; USD 166,000 - 221,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits package

Job summary

Atlassian is seeking a Senior ML System Engineer for the GenAI Platform to build and maintain the infrastructure powering ML models and pipelines. You will enable ML teams to train, evaluate, deploy, and operate models at scale.

You will lead engineers on complex projects, collaborate across teams, and help shape architecture and outcomes for GenAI initiatives. Strong programming, distributed systems, and cloud experience are essential.

Qualifications

• 5+ years of experience as a software developer.
• Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin and Python).
• Experience with Continuous Delivery and Continuous Integration.
• Experience building and operating large scale distributed systems using AWS services.
• Experience with distributed large-scale data processing (preferably Apache Spark).
• Basic understanding of Machine Learning projects lifecycle.

Responsibilities

• Lead other engineers to drive projects from design to launch.
• Collaborate with other teams and internal customers to set expectations and communicate results.
• Build and maintain core infrastructure to enable ML engineers and data scientists to train, evaluate, deploy, and operate ML models and pipelines.

Skills

5+ years experience

OO language fluency

CI/CD

Distributed systems (AWS)

Spark data processing

ML lifecycle basics

Tools

AWS (S3, Kinesis, CloudFormation, EKS)

Apache Spark

Databricks

Job description

Engineering | Remote, Americas | Remote, Remote | San Francisco, United States | Austin, United States | Mountain View, United States or Remote | New York, United States | Full-Time

Working at AtlassianAtlassians 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.

As a Senior ML System Engineer in the Rovo GenAI Platform team, you will build and maintain the core infrastructure to allow machine learning engineers and data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines, and power the GenAI products in Atlassian. You will use your software development expertise to solve difficult problems, tackling complex infrastructure and architecture challenges.

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.

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:

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: $206,100 - $269,075

Zone B: $185,490 - $242,168

Zone C: $171,063 - $223,332

On your first day, we’ll expect you to have

5+ years of experience as a software developer.

Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin and Python).

Experience with Continuous Delivery and Continuous Integration.

Experience building and operating large scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking).

Experience with distributed large-scale data processing (preferably Apache Spark).

Basic understanding of Machine Learning projects lifecycle.

It would be great, but not required if you have

Expert-level with search platform, deep learning training/inference platfrom.

Experience with Databricks.

Experience with scaling and deploying Machine Learning models.

Don’t see an exact role match? No problem! Join our Talent Community and stay up-to-date on company and careers updates relevant to your career.