The mission of Atlassian is to unleash 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. AI/ML is significantly transforming how teams come together to plan, track, and deliver work across software and business teams using our products. We are looking for rockstar Machine learning engineers to come help us to further this mission and help make teams more productive leveraging AI across our product portfoilo.
As an Applied Machine Learning engineer, you will work on the development and implementation of the cutting edge machine learning algorithms, training models, collaborating with product, engineering, and analytics teams, to build the AI functionalities into each Atlassian products and services. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations. You will be responsible for application of AI/ML to various product problems to improve Atlassian products and actively contribute to Atlassian Intelligence features.
Master or PhD in Machine Learning, AI, Information retrieval or quantitative subjects (Statistics, Mathematics, Computer Science, Operations Research) or equivalent relevant work experience in data science domain.Expertise in Python or Java with and the ability to write performant production-quality code, familiarity with SQL. Knowledge of Spark and cloud data environments is a plus (e.g. AWS, Databricks)Experience building and scaling machine learning models using large amounts of dataAgile 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 spaceExperience in developing deep learning-based models and working on LLM-related applicationsExcelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions