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Atlassian is seeking a Machine Learning Engineer to join our Growth organization. Growth builds intelligent, personalized experiences that help customers discover value, adopt more of Atlassian, and progress through the customer lifecycle, from awareness and activation to expansion, retention, and long-term value. You will help turn behavioral and product signals into scalable ML systems that support the growth funnel, drive meaningful engagement, and enable more relevant customer and sales experiences.
Your future team
The Growth organization brings together product, engineering, data science, analytics, and product operations to improve how customers discover, adopt, and expand their use of Atlassian. We work across the full funnel, from acquisition and onboarding through activation, conversion, expansion, and retention. Our teams use experimentation, personalization, and intelligent orchestration to personalize and help customers see the right product, feature, or next step at the right time, all while creating durable business value.
As part of Growth, you will build ML capabilities that enable teams to deliver personalized and consistent, measurable experiences across Atlassian's portfolio. This includes building reliable data foundations, features, models, evaluation frameworks, and decisioning systems that support cross-product recommendations and personalized journeys; for example, moving cross-flow ranking from fragmented, fixed heuristics toward a unified, value-aware orchestration system that ranks recommendations using user context, probability of conversion, and expected lifetime value, going from generic, noisy messaging to actionable and personalized recommendations that improve customer outcomes and business impact across surfaces such as navigation, screen-space flags, and app-switcher experiences.
What you'll do
As a Machine Learning Engineer, you will design, build, and operate ML systems that help Growth make better decisions across the customer and sales funnel. You will develop models and decisioning services for personalized recommendations, engagement and activation journeys, cross-product expansion, and sales experiences, providing contextual, proactive support throughout the funnel. You will define the strategy on how our ML capabilities should evolve to support Atlassian short, mid, and long-term goals and drive their implementation.
You will partner closely with product, engineering, data science, analytics, marketing, and sales teams to translate ambiguous growth opportunities into measurable experiments and production capabilities. Your work may include designing models and system architectures; building datasets, features, and evaluation frameworks; running offline policy evaluation and online experiments; monitoring attribution, latency, quality, and fairness; and iterating based on customer and outcomes. You will help ensure that we optimize for durable customer and portfolio value, not only short-term clicks or conversions.
Your background
On the first day, we'll expect you to have
- Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience)
- 5+ years of related industry experience in the machine learning domain
- Expertise in Python, and knowledge about other languages such as Java and Typescript, with the ability to write performant production-quality code, familiarity with SQL, 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
- Experience building datasets and evals to benchmark systems operating at a large scale
- Ability to communicate and explain ML 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
- Experience 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 partnering with product, analytics, marketing, or sales teams to build personalized customer journeys or sales-assist experiences
- Familiarity with contextual bandits, uplift modeling, recommender systems, policy evaluation, causal inference, or other approaches for optimizing decisions under uncertainty
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 applying machine learning to growth, personalization, recommendations, ranking, experimentation, or decisioning problems across a customer funnel
- Understanding of engagement, activation, conversion, expansion, and retention metrics, and how to balance short-term signals with downstream outcomes
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
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.
This role may also be eligible for benefits, bonuses, commissions, and equity.
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: $206,100 - $269,075
Zone B: $185,490 - $242,168
Zone C: $171,063 - $223,332
Benefits & Perks
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 go.atlassian.com/perksandbenefits .
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 .
In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.
Skills Required
- Bachelor’s or Master’s degree, preferably in Computer Science, or equivalent experience
- 5+ years of related industry experience in machine learning
- Expertise in Python and ability to write performant, production-quality code
- Knowledge of Java and TypeScript
- Familiarity with SQL, Spark, and cloud data environments such as AWS or Databricks
- Experience building and scaling machine learning models in business applications using large amounts of data
- Experience building datasets and evaluation frameworks to benchmark systems at scale
- Ability to communicate and explain machine learning concepts to diverse audiences
- Experience solving ambiguous and complex problems and developing innovative solutions
- Experience partnering with product, analytics, marketing, or sales teams on personalized customer journeys or sales-assist experiences
- Agile development mindset and commitment to iterative improvement
- Familiarity with contextual bandits, uplift modeling, recommender systems, policy evaluation, causal inference, or related decision-optimization approaches
- Experience in consumer or B2C SaaS, or enterprise/B2B environments
- Experience applying machine learning to growth, personalization, recommendations, ranking, experimentation, or decisioning across a customer funnel
- Understanding of engagement, activation, conversion, expansion, and retention metrics
Atlassian Compensation & Benefits Highlights
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Parental & Family Support — 26 weeks paid leave for birthing parents and 20 weeks for non‑birthing parents are offered, alongside inclusive family‑formation support such as fertility, adoption, and surrogacy. Additional resources include neurodiverse family support and conveniences like breastmilk shipping for business travel.
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Healthcare Strength — Medical, dental, and vision coverage is paired with extensive mental‑health programs (e.g., Modern Health/EAP), plus disability and life insurance in many locations. Fertility and family‑formation benefits further expand the health offering.
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Retirement Support — A 401(k) with a 4% company match and 100% immediate vesting is highlighted for U.S. employees. Retirement planning support is also included.
Atlassian Insights
What We Do
Atlassian creates teamwork solutions for high-performing teams. Our portfolio of collaboration and work management software products includes Jira, Confluence, Trello, Loom and Rovo. More than 300,000 businesses worldwide rely on Atlassian’s technology, including 80 percent of Fortune 500 companies. Our solutions support various business teams and they help organizations plan, track, and deliver their biggest ideas together.
Why Work With Us
At Atlassian, we believe we can accomplish so much more together than apart — which is why everything from our tooling — to our distributed workforce — to how our teams are structured is rooted in collaboration. Come join us and help unleash the potential of every team.
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