Senior Machine Learning Engineer, Search & Intelligence

Senior Machine Learning Engineer, Search & Intelligence Atlassian is looking for a Senior Machine Learning Engineer to join our Search & Intelligence organization. Our team builds the intelligent experiences, agentic systems, models, evaluation frameworks, and data pipelines that power Atlassian's AI products and accelerate AI innovation across the company. As a Senior Machine Learning Engineer, you will lead the development and productionization of advanced machine learning systems that improve how people discover, understand, and act on knowledge across Atlassian. You will work across the full machine learning lifecycle, from problem definition and data exploration to model development, experimentation, evaluation, deployment, and ongoing optimization. You will partner closely with product managers, software engineers, data scientists, and other technical stakeholders to translate ambiguous product challenges into scalable AI solutions. You will contribute to architectural decisions, raise engineering and scientific standards, and mentor other machine learning engineers. Your work will help deliver intelligent search, recommendations, conversational experiences, and other AI capabilities used by Atlassian customers worldwide. 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 - $223,332On your first day, we'll expect you to have: A Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience. At least 5 years of professional experience developing and deploying machine learning or data science solutions in production. Strong programming skills in Python and one or more production languages such as Java, Kotlin, or TypeScript. Strong knowledge of SQL and experience working with large-scale data processing technologies such as Spark. Experience designing, training, evaluating, deploying, and scaling machine learning models using large and complex datasets. Experience building performant, reliable, and maintainable production-quality software. Familiarity with cloud-based data and machine learning environments, such as AWS, Databricks, or comparable platforms. Experience designing evaluation strategies and using metrics, experimentation, and error analysis to guide model and product improvements. Experience collaborating effectively across product, engineering, analytics, and data science teams. An ability to independently navigate ambiguous and complex problems, break them into manageable components, and deliver practical solutions. Strong written and verbal communication skills, with the ability to explain complex technical concepts clearly. An agile development mindset and an appreciation for rapid iteration, continuous improvement, and learning from results. It's great, but not required, if you have: End-to-end experience integrating machine learning or AI capabilities into customer-facing products. Experience building search, recommendation, ranking, personalization, or natural language processing systems. Experience developing deep learning models and applying large language models to production use cases. Experience with agentic systems, tool-using models, or multi-step reasoning and planning systems. Experience fine-tuning, evaluating, monitoring, and optimizing large language models. Experience working in a consumer or B2C environment, a SaaS product organization, or an enterprise B2B environment. Experience with ML platforms, model serving, feature stores, data pipelines, observability, or responsible AI practices. A track record of technical leadership, influencing architecture and strategy beyond your immediate team, and mentoring other engineers. Experience balancing long-term technical investments with pragmatic delivery in an evolving product environment.