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.
With a sufficient timezone overlap with the team, we're able to hire eligible candidates for this role from any location in Australia. If this sparks your interest, apply today and chat with our friendly Recruitment team further.
Atlassian is looking for an experienced and visionary Principal Machine Learning Engineer to join our FinOps Insight team based in Australia.
Your future team
We are a team of people with backgrounds in FinOps Analysts and Data Engineers. We operates within the Cloud FinOps organisation, which is part of the Core Engineering department.
Our org is on a mission to drive cost-efficiency to sustain Atlassian's growth with our team focusing on bringing relevant data and compelling insights, helping teams make informed decisions and sustain their unit economics.
As a Principal Machine Learning Engineer, reporting to Senior Engineering Manager -FinOps Insight, you'll drive our technical vision and lead the development of scalable ML solutions that align with our cost-efficiency strategy. This role is ideal for someone who is both strategic and hands-on, and for someone who thrives on curiosity, enjoys solving complex problems, and is passionate about harness the power of AI to accelerate time to impact without scaling up teams
What You'll Do
- Drive the development and implementation of the cutting edge machine learning algorithms, training sophisticated models that power financial insights, including anomaly detection, forecasting, and NLP-driven analytics on financial health
- Develop scalable ML pipelines to support timely anomaly detection and cost optimisation.
- Design system and model architectures, conduct rigorous experimentation and model evaluations
- Work closely with data engineers to aggregate and structure cloud financial data for effective ML applications.
- Ensure MLOps best practices, including model deployment, monitoring, and continuous learning
- Collaborate with FinOps Analysts, engineering, and product teams to translate ML insights into business impact.
- Collaborate with cross-functional teams to integrate AI-driven intelligence into our tooling
- Optimise models for performance, interpretability and efficiency in real-work applications
- Coach data engineers, fostering a culture of learning and innovation in ML and AI
- Master or PhD in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience)
- 5+ years of related industry experience in the data science domain
- Expertise in anomaly detection, forecasting models, NLP, and optimisation techniques.
- Proficiency in ML frameworks (e.g.TensorFlow, PyTorch, Scikit-Learn) and MLOps tools.
- Strong programming skills in Python, SQL and with the ability to write performant production-quality code, experience with Spark, cloud platforms and data environment (AWS, GCP, Azure / Databricks)
- Deep knowledge of ETL and software engineering tools, incl. Kafka and Airflow
- Ability to balance innovation with practical execution, delivering solutions that drive measurable impact.
- Ability to communicate and explain data science concepts to diverse audiences and translate ML insights into actionable cost efficiency strategies, craft a compelling story
- Experience building and scaling machine learning models in business applications using large amounts of data
- Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognise 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
- Familiarity with FinOps and cloud financial management
- Hands-on experience with cloud cost attribution, cost modelling and optimisation.
- Experience with agent-based AI frameworks like CrewAI and Langchain, along with LLMs and LGMs
- 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
Our perks & benefits
Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit go.atlassian.com/perksandbenefits to learn more.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the 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.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
To learn more about our culture and hiring process, visit go.atlassian.com/crh .
