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As a Machine Learning engineer, you will independently work on the development and implementation of the cutting edge machine learning algorithms, training sophisticated models, collaborating with engineering and analytics teams, to build the AI functionality for Atlassian. Your daily responsibilities will encompass a broad spectrum of tasks such as understanding system and model architectures, conducting rigorous experimentation and model evaluations and dealing with related problems. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across Atlassian products and platforms.
Job Responsibility:
Development and implementation of the cutting edge machine learning algorithms
Training sophisticated models
Collaborating with engineering and analytics teams
Understanding system and model architectures
Conducting rigorous experimentation and model evaluations
Dealing with related problems
Requirements:
Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience)
5+ years of related industry experience in the data science domain
Exposure in Python or Java with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)
Exposure to 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
Nice to have:
End to end exposure of integrating AI/ML capabilities in products ( frontend or backend tech stack)
Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
Experience in independently dealing with 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
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