At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate’s skills, expertise, or experience. In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:

Zone A: $192,600 – $267,700

Zone B: $173,400 – $241,000

Zone C: $159,900 – $222,200

This role may also be eligible for benefits, bonuses, commissions, and equity.

Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.

 

What you’ll do

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.

 

 

On your first day, we’ll expect you to have

  • Bachelor’s or Master’s degree (preferably a Computer Science degree or equivalent experience).
  • 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 data
  • 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
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