Note: The job is a remote job and is open to candidates in USA. Atlassian develops software products that help teams collaborate and work effectively. The company is seeking a Senior Machine Learning Engineer to design, build, and operate scalable ML systems for personalized recommendations, customer engagement, activation, expansion, retention, and sales experiences. The role partners with cross-functional teams to translate growth opportunities into experiments and production capabilities while defining the evolution of ML capabilities.
Responsibilities
- Design, build, and operate ML systems that help Growth make better decisions across the customer and sales funnel
- 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
- Define the strategy on how our ML capabilities should evolve to support Atlassian short, mid, and long-term goals and drive their implementation
- Partner closely with product, engineering, data science, analytics, marketing, and sales teams to translate ambiguous growth opportunities into measurable experiments and production capabilities
- 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
- Help ensure that we optimize for durable customer and portfolio value, not only short-term clicks or conversions
Skills
- 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
- 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
Benefits
- Atlassians can choose where they work, whether in an office, from home, or a combination of the two, giving them the flexibility to balance business responsibilities and support their families.
- This role may also be eligible for benefits, bonuses, commissions, and equity.
- Health and wellbeing resources
- Paid volunteer days
Company Overview
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