Machine Learning Manager

General Responsibilities

• Strategic Leadership: Define and execute the long-term AI/ML strategy, ensuring alignment with product and business goals.

• Team Building & Talent Development: Recruit, coach, and develop a high-performing team of engineers and scientists, fostering an inclusive and innovative culture.

• Stakeholder Management: Partner with cross-functional leadership (product, engineering, data science) to drive product vision and execution.

• Performance Management: Oversee team performance, providing coaching, feedback, and career growth opportunities for direct reports.

• Technical Leadership & Mentoring: Provide technical guidance and mentorship to engineering teams, ensuring high standards of code quality and technical excellence.

Daily Responsibilities

• Project Oversight: Oversee the end-to-end lifecycle of key AI/ML initiatives, ensuring timely delivery and high-quality standards.

• Resource Allocation: Balance team bandwidth across competing priorities, ensuring optimal resource distribution for high-impact projects.

• Process Optimization: Establish and refine engineering processes to improve team velocity, code quality, and deployment standards.

• Risk Management: Proactively identify technical and operational risks, implementing mitigation strategies to maintain team momentum.

• Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience)

• 10+ years of related industry experience in the data science domain, including 5+ years of direct people management experience. You should have a proven track record of building, mentoring, and scaling high-performing machine learning teams, with deep experience in organizational strategy, performance management, and developing engineering leaders.

• 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

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

It's great, but not required, if you have

• Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space

• Experience in developing deep learning-based models and working on LLM-related applications

• Excelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions.

Benefits & Perks

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.

In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.