Principal Machine Learning Engineer

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

At DevInfra Transformations, we enable teams to ship quality at velocity. Our focus is to "Build an industry-leading internal platform. Validate our hypothesis with data. Ship features for internal and external usage". This is accomplished by building complete end-to-end ML enabled development cycle and leveraging AI capabilities extensively. This is a unique opportunity to work in a collaborative environment, implement the cutting edge machine learning techniques, especially forecasting modelings, and tackle challenging and distinctive problems.

• As a Principal 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.

• 10+ years of total experience, 5+ years of related industry experience in the MLE / data science domain
• Fluency in Python
• Solid understanding of machine learning concepts and algorithms, including supervised and unsupervised learning, deep learning, and NLP.
• Familiarity with popular ML libraries like sci-kit-learn, Keras/TensorFlow/PyTorch, numpy, pandas
• Good Understanding of Machine Learning project lifecycle
• Experience in architecting and implementing high-performance RESTful microservices ( API development for ML Models )
• Familiarity with MLOps and experience with scaling and deploying Machine Learning models
• 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
• Experience in model fine tuning, data collection, reinforced learning, synthetic data generation, feedback loop, latency / accuracy improvements, quantisation etc
• Ability to lead independently

• 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.
• Experience or passion on building cutting edge developer tools products with AI/ML