Senior Machine Learning Engineer

Senior Machine Learning Engineer – 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.

The Central AI org is part of the larger Atlassian Intelligence program. Its purpose is to accelerate AI innovation across all our products and platform, provide cohesive AI experiences and set up an Atlassian AI infrastructure for the future.

While it’s anticipated that the majority of AI‑driven initiatives will be developed and executed by federated product teams within Atlassian, the role of Central AI is pivotal to this process. Central AI is tasked with constructing the underlying infrastructure and capacities, which are crucial for the seamless integration and optimal functionality of AI across various departments. By doing so, Central AI ensures that different teams within the organization do not work in silos but have access to a unified foundation that promotes efficiency and collaboration.

Additionally, Central AI is responsible for developing some of the core shared experiences typical in the AI domain, such as search, knowledge discovery and conversation.

As a Senior Machine Learning engineer, you will work on the development and implementation of cutting‑edge machine learning algorithms, train sophisticated models, and collaborate with product, engineering, and analytics teams to build the AI functionalities into each Atlassian product and service. Your daily responsibilities will encompass: designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to junior ML engineers.

Your role is pivotal, stretching beyond these tasks, ensuring AI’s transformative potential is realized across our offerings.

On the first day, we’ll expect you to have:

• Bachelor’s or Master’s degree (preferably Computer Science or equivalent experience).
• 3+ years of related industry experience in the data science domain.
• Expertise in Python or Java with the ability to write performant production‑quality code, familiarity with SQL, and knowledge of Spark and cloud data environments (e.g. AWS, Databricks).
• Experience 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; a very high bar for output quality, but recognition of the business benefit of “having something now” vs “perfection sometime in the future.”
• 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.

At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. For this role, our current base pay ranges for new hires in each zone are:

• Zone A: $202,500 – $264,375
• Zone B: $182,700 – $238,525
• Zone C: $168,300 – $219,725

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

Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit .

At Atlassian, we’re motivated by a common goal: to unleash the potential of every team. Our software products help teams around the world and our solutions are designed for all types of work. Team collaboration through our tools makes what may be…