Atlassian is looking to improve the performance, scalability, and robustness of their Recommendation system and other AI/ML models.
Requirements
- Experience building and scaling machine learning models in business applications using large amounts of data
- Agile development mindset, appreciating the benefit of constant iteration and improvement
- 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'
- Experience with machine learning engineering teams running core services at scale
- Experience with quantitative subjects (Computer Science, Mathematics, Statistics, Operations Research)
Responsibilities
- 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 team members on best practices, code quality, design patterns, testing, debugging, and documentation.
- Communicate effectively with internal and external partners, present technical concepts and results clearly and concisely, and solicit feedback and input from various stakeholders.
Other
- Hire, onboard, and retain top talent for your team and foster a culture of innovation, collaboration, and excellence.
- 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
- Ability to work with the product managers, Growth engineering teams, Performance Marketing online marketers, Data Science and Data Engineering teams
