Senior Machine Learning Engineering Manager

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. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Your future team
The GenAI foundation and quality team sits within the Search and AI Conversation Group in the Atlassian Central AI Organization. We work cross-functionally across stakeholders in Growth, GTM, Product, Finance and Sales organizations, providing generative AI, machine learning infrastructure and modeling applications. Our team consists of ML engineers and system engineers, and provides many opportunities for collaboration, knowledge sharing, and individual growth. We are highly nimble, with a focus on velocity between conceptualization and initial output, and laser-focused on business impact.
What you'll do
As the engineering manager, you will need to work with the product managers, Growth engineering teams, Performance Marketing online marketers, Data Science and Data Engineering teams to:

• Manage the end-to-end machine learning lifecycle, from data collection and preprocessing, to model development and deployment, to evaluation and monitoring.
• Research and implement novel machine learning techniques and algorithms that can improve the performance, scalability, and robustness of our Recommendation system, and other AI/ML models.
• Mentor and coach your team members on best practices, code quality, design patterns, testing, debugging, and documentation.
• Hire, onboard, and retain top talent for your team and foster a culture of innovation, collaboration, and excellence.
• Communicate effectively with internal and external partners, present technical concepts and results clearly and concisely, and solicit feedback and input from various stakeholders.

Your background

• Master or PhD in a quantitative subject (Computer Science, Mathematics, Statistics, Operations Research, or relevant work experience)

• 5+ years of experience managing machine learning engineering teams running core services at scale

• Experience building and scaling machine learning models in business applications using large amounts of data

• Ability to communicate and explain data science concepts to diverse audiences, craft a compelling story

• Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future"

• Agile development mindset, appreciating the benefit of constant iteration and improvement

Our perks & benefits
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits .
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
To learn more about our culture and hiring process, visit go.atlassian.com/crh .