Senior machine learning engineer

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. Senior Machine Learning Engineer — Agentic Search & Query Intelligence Atlassian is seeking a Senior Machine Learning Engineer to join our Query Intelligence team, working on Agentic Search and Search Relevance. You will build intelligent systems that help people and AI agents understand complex questions, discover relevant knowledge, and accomplish tasks across Atlassian products and connected tools. Your future team Our team is part of Search Relevance within Intelligence & Experience. We build the intelligence that connects what users and agents are trying to accomplish with the information they need. Our work spans query understanding, search planning, and agentic retrieval. We develop capabilities that interpret user intent, break complex requests into actionable searches, incorporate organizational context, and refine search strategies as new evidence becomes available. These capabilities support experiences across Rovo Search, Rovo Chat, and AI agents. We work closely with product, search infrastructure, modeling, and evaluation teams. We combine applied research with production engineering, using experimentation and customer feedback to improve search quality, reliability, and efficiency. What you’ll do Develop machine learning and LLM capabilities for query intelligence, including intent understanding, query rewriting and decomposition, entity understanding, and translating natural language into structured search constraints. Build and improve agentic search planners that turn complex requests into search strategies, select appropriate sources and tools, and adapt based on retrieved evidence. Improve model and agent behavior through prompt development, model selection, training data improvements, and fine-tuning where appropriate. Own projects from problem definition and prototyping through experimentation, production deployment, and ongoing measurement. Build datasets and evaluation methods, partnering with evaluation teams to measure retrieval relevance, evidence coverage, task success, and grounding. Use offline analysis and online experiments to diagnose failures and validate improvements. Balance search quality with latency, inference cost, and reliability, building systems that operate effectively within enterprise permissions and data boundaries. Collaborate with search platform, relevance, Rovo Chat, and other AI teams to integrate query intelligence and agentic search capabilities into customer experiences. Contribute to technical design and code reviews, mentor junior engineers, and share learnings that strengthen the team’s engineering and ML practices. Your background On the first day, we’ll expect you to have A bachelor’s or master’s degree in Computer Science or a related field, or equivalent practical experience. 4+ years of relevant industry experience in machine learning, with experience delivering ML capabilities into production. Strong Python programming skills and the ability to write reliable, maintainable, production-quality code. Experience in one or more of natural language processing, information retrieval, search relevance, or LLM applications. Experience designing experiments, building evaluation datasets, analyzing model behavior, and using evidence to guide improvements. An understanding of the ML development lifecycle, from data preparation and modeling to deployment, monitoring, and iteration. The ability to take ownership of ambiguous problems, make practical technical tradeoffs, and communicate clearly with engineering and product partners. It’s great, but not required, if you have Experience building AI agents, tool-use workflows, multi-step search systems, or retrieval-augmented generation applications. Experience with query understanding, semantic or hybrid retrieval, ranking, personalization, or context-aware search. Experience with LLM fine-tuning or post-training, including supervised fine-tuning, preference optimization, or reinforcement learning. Experience developing evaluation approaches for agents, including trajectory analysis, human evaluation, or model-based judging. Experience with distributed data processing and cloud ML environments such as Spark, AWS, or Databricks. 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.