Principal Machine Learning Engineer

Role Description

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
• Providing guidance to emerging ML engineers

Your role is pivotal, ensuring AI's transformative potential is realized across our offerings.

Qualifications

• Experience in machine learning model development and deployment
• Strong technical leadership skills
• Ability to mentor and guide junior and senior engineers
• Excellent communication skills for both technical and non-technical stakeholders

Requirements

• 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
• Design, develop, and deploy production-grade ML models (e.g., ranking, retrieval, LLM-based systems)
• 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
• 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
• Mentor and guide junior and senior engineers, fostering a culture of innovation, collaboration, and continuous learning
• Identify, solve, and bridge gaps/problems across teams using experience and expertise
• 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

Benefits

• Wide range of perks and benefits designed to support you and your family
• Health and wellbeing resources
• Paid volunteer days
• Eligibility for benefits, bonuses, commissions, and equity