Principal Machine Learning Engineer

Engineering | San Francisco, United States | Remote, Remote

Working at Atlassian

Atlassians 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.

As part of our team, you will play a crucial role in innovating the core intelligence solutions within our DevAI products. Your responsibilities will include (but not limited to) LLM integration, prompt engineering, and developing end-to-end AI features using cutting-edge technologies. You will collaborate closely with a diverse and highly skilled group of scientists and software engineers within our team, as well as with multiple partner teams across the company. Together, we are committed to delivering Atlassian's world-class developer AI products that will shape the future of software development.

Responsibility

General Responsibilities

These are ongoing or overarching tasks that guide the strategic and collaborative aspects of the role:

• Problem Solving: Identify complex challenges and provide creative solutions to advance the capabilities and functionalities of the products.
• Collaboration: Work with cross-functional teams, including data scientists and software engineers. Build and maintain sustainable partnerships with team members from various technical backgrounds.
• Communication: Communicate technical details effectively to the team and engage in technical discussions to contribute ideas and solutions.
• Continuous Learning: Stay updated with the latest research and advancements in machine learning, AI, and relevant technology applications. Apply cutting-edge knowledge and techniques to enhance product innovation and effectiveness.

Daily Responsibilities

These tasks are more routine or technical, involving hands-on activities that need to be performed regularly:

• Design and Development: Design LLM based methodology and algorithms tailored to specific product needs.
• Data Handling: Perform data preprocessing and feature engineering to improve product inputs and performance.
• Evaluation: Conduct experiments to evaluate the performance of products and use a variety of metrics and testing methods to ensure the solutions meet design specifications.
• Implementation and Optimization: Implement and optimize machine learning pipelines.
• Monitoring and Maintenance the deployed intelligence solutions to ensure they continue to perform accurately and efficiently.

At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.

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