Principal Machine Learning Engineer - Search & Intelligence

Atlassian is a global leader in team collaboration and productivity software. The company is seeking a Principal Machine Learning Engineer to lead the development and implementation of machine learning algorithms and models powering AI capabilities across its products and services. The role involves designing system and model architectures, leading experimentation and evaluation, mentoring ML engineers, and helping shape Atlassian’s AI strategy.

Responsibilities:

• As a Principal Machine Learning Engineer, you will lead the development and implementation of cutting-edge machine learning algorithms and sophisticated models that power AI capabilities across Atlassian’s products and services
• You will collaborate closely with product, engineering, and analytics teams to translate complex business and customer needs into impactful solutions
• Your responsibilities will span designing system and model architectures, leading rigorous experimentation and evaluation, and providing technical mentorship to emerging ML engineers
• Beyond these core responsibilities, you will help shape our AI strategy and ensure its transformative potential is realized across Atlassian

Requirements:

• A bachelor's or master's degree in computer science or a related field, or equivalent practical experience
• At least five years of relevant industry experience in machine learning, data science, or a related discipline
• Strong programming skills in Python and one or more production languages such as Java, Kotlin, or TypeScript
• Proficiency in SQL and experience with Spark and cloud-based data environments such as AWS or Databricks
• Experience building, deploying, and scaling machine learning models for business applications using large, complex datasets
• Strong communication skills, including the ability to explain data science concepts to diverse audiences and tell compelling, data-driven stories
• A pragmatic, business-focused approach. You hold a high bar for quality while applying the 80/20 principle and recognizing when delivering a valuable solution today is better than pursuing perfection later
• An agile mindset and an appreciation for continuous iteration, learning, and improvement
• Experience fine-tuning, post-training, and optimizing state-of-the-art large language models, embedding models, and ranking models
• Experience developing and evaluating advanced agentic AI systems, including tool-using agents capable of planning, multi-step reasoning, and autonomous task execution
• Experience working in consumer or B2C environments, SaaS, or enterprise and B2B products
• A track record of solving ambiguous and complex problems by navigating uncertainty, breaking challenges into manageable components, and developing innovative, practical solutions