Senior Machine Learning Engineer - Growth

About the role

Atlassian is looking for a Senior Machine Learning Engineer to join its Growth organization, which builds intelligent, personalized experiences that help customers discover value, adopt more of Atlassian and move through the customer lifecycle. You will turn behavioral and product signals into scalable ML systems that support the growth funnel, drive engagement and enable more relevant customer and sales experiences. The role is open to Seattle, San Francisco and remote candidates.

Key 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.
• Define the strategy for how ML capabilities evolve to support Atlassian's short, mid and long-term goals.
• Partner with product, engineering, data science, analytics, marketing and sales teams to turn growth opportunities into measurable experiments and production capabilities.
• Build datasets, features and evaluation frameworks, run offline policy evaluation and online experiments, and monitor attribution, latency, quality and fairness.
• Help move cross-flow ranking toward a unified, value-aware system that uses user context, probability of conversion and expected lifetime value.

Required profile

• Bachelor's or Master's degree (preferably Computer Science or equivalent experience).
• 5+ years of related industry experience in the machine learning domain.
• Experience building and scaling ML models in business applications with large amounts of data, and building datasets and evaluations for large-scale systems.
• Experience partnering with product, analytics, marketing or sales teams on personalized customer journeys or sales-assist experiences.
• Ability to explain ML concepts to diverse audiences and focus on business practicality.
• Agile mindset and experience solving ambiguous, complex problems.
• Nice to have: consumer or B2B SaaS experience, and experience applying ML to growth, personalization, recommendations, ranking, experimentation or decisioning.

Required skills

• Python expertise, with knowledge of Java and TypeScript and the ability to write production-quality code.
• Familiarity with SQL and Spark.
• Cloud data environments such as AWS and Databricks.
• Nice to have: contextual bandits, uplift modeling, recommender systems, policy evaluation, causal inference.

What we offer

• Base pay for new hires in Zone A of $206,100-$269,075, Zone B of $185,490-$242,168 and Zone C of $171,063-$223,332.
• Possible eligibility for benefits, bonuses, commissions and equity.
• Health and wellbeing resources and paid volunteer days.