Senior Machine Learning Engineer

Overview

At Atlassian, employees have flexible work arrangements, allowing them to work from office locations, home, or a hybrid setup based on personal priorities and needs. The company hires professionals in countries where it operates legally.

Team and Work Environment

This role is part of the AI Context team operating within the larger Rovo + AI organization, spread across Sydney, Melbourne, Brisbane, and the US West Coast. The team includes software and machine learning engineers collaborating closely with related divisions to develop AI-driven features that enhance personalized and context-aware user experiences. Engineers are given considerable autonomy, promoting asynchronous collaboration and minimal but effective alignment.

Role Responsibilities

• Design, develop, deploy, and maintain agentic large language model (LLM) harness solutions that empower prominent AI features within Atlassian's product suite.
• Continuously enhance system quality and reduce operational costs of LLM-based production systems.
• Build thorough evaluation frameworks to assess and improve model performance.
• Contribute to specialized areas including fine-tuning language models and efficient model serving.
• Drive technical leadership by shaping the long-term architecture for LLM harness engineering, integrating advances from research and industry.
• Address complex technical challenges, plan sustainable system improvements, and implement them end-to-end.
• Collaborate with engineering leadership and multiple stakeholder teams to influence technical directions.
• Lead virtual teams accountable for critical system components and mentor junior engineers to help meet team goals.

Qualifications and Requirements

• Bachelor’s or Master’s degree in Computer Science or a closely related discipline, or comparable practical experience.
• At least 4 years of professional experience working with machine learning, specifically in designing, evaluating, and managing LLM or agentic systems in production settings.
• Proficiency in Kotlin and/or Python, capable of writing efficient, production-grade code with modern AI-assisted development tools.
• Hands-on experience operating machine learning systems in live environments, including applying best practices for reliability, quality, and cost optimization.
• Expertise in constructing datasets, benchmarking tools, and evaluation protocols at scale; familiarity with SQL, distributed data processing, and cloud-based data services.
• Strong sense of ownership with a proven track record of advancing complex technical projects from conception through deployment and operational management.
• Excellent communication and interpersonal skills to effectively explain machine learning concepts and influence cross-team technical strategies.
• Experience leading technical initiatives and mentoring engineers within collaborative or virtual teams.
• An iterative and pragmatic mindset focused on balancing high standards with delivering incremental improvements.

Preferred but Not Mandatory

• Experience in fine-tuning smaller language models.
• Familiarity with serving and managing LLMs using platforms like NVIDIA Triton Inference Server.
• Experience applying machine learning techniques to personalization or context-aware product features.
• Background in solving complex problems in enterprise SaaS or large-scale product environments.

Benefits and Culture

Atlassian provides a diverse set of benefits aimed at supporting employees' well-being, family needs, and community involvement. These include resources for health and wellness, paid volunteer days, and additional perks. The company values inclusivity and equal opportunity, ensuring a discrimination-free workplace. Accommodations are offered during recruitment to support candidates' needs. Employment includes identity verification processes to ensure authenticity in hiring.

About Atlassian

Driven by the mission to unlock team potential globally, Atlassian's software solutions facilitate collaboration across various work types, making challenging tasks achievable collectively. Their culture embraces diversity and equity without bias based on identity, orientation, or status.