Principal ML Systems Engineer - Scalable AI & Evaluation

Atlassian Corp.; San Francisco (CA); Remote; USD 237,000 - 309,000; Full time

Benefits offered by this job

Health and wellbeing resources

Volunteer days

Equity and benefits

Job summary

Atlassian is seeking a Principal Machine Learning Engineer to lead the Rovo Chat Quality team. You will architect and ship production ML systems, set evaluation standards, and push the boundaries of agentic AI across Atlassian’s products.

You will drive technical direction, mentor engineers, and collaborate across ML, engineering, product, analytics, research, and design to deliver measurable customer impact at scale.

Qualifications

• Architect and ship large‑scale ML/AI systems delivering measurable business impact.
• Deep experience with LLMs, agentic systems, evaluation, experimentation, and dataset development.
• Strong production engineering skills; able to stay hands‑on in a modern ML stack.
• Principal‑level leadership: set direction and lead complex initiatives from ambiguity to production.
• Excellent product and technical judgment balancing quality, speed, reliability, safety, latency, and cost.

Responsibilities

• Lead open‑ended technical problems to improve Rovo Chat quality and customer value.
• Set the technical vision for evaluating and improving Rovo Chat and related products.
• Architect and build production ML/evaluation systems at scale with data, tests, and signals.
• Drive improvements across reasoning, planning, tool use, memory, and long‑horizon execution.
• Collaborate across ML, engineering, product, analytics, research, and design to create clarity and momentum.

Skills

Large-scale ML systems

LLM-powered products

Production engineering

Technical leadership

Communication skills

Job description

Atlassian is seeking a Principal Machine Learning Engineer to lead the Rovo Chat Quality team. You will architect and ship production ML systems, set evaluation standards, and push the boundaries of agentic AI across Atlassian’s products.

You will drive technical direction, mentor engineers, and collaborate across ML, engineering, product, analytics, research, and design to deliver measurable customer impact at scale.