Develop and deploy machine learning algorithms and models for Atlassian products. Design model and system architectures, run experiments and evaluations, solve product problems with AI/ML, and contribute to Atlassian Intelligence features. Collaborate with product, engineering, and analytics teams while building scalable, production-quality solutions using large datasets, deep learning, and LLM-related applications.
Engineering | Seattle, United States | Remote, Remote | Full-Time
Working at AtlassianAtlassians 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. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.Your Future TeamThe mission of Atlassian is to unleash 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. AI/ML is significantly transforming how teams come together to plan, track, and deliver work across software and business teams using our products. We are looking for rockstar Machine learning engineers to come help us to further this mission and help make teams more productive leveraging AI across our product portfolio.
What you'll doAs a Machine Learning engineer, you will work on the development and implementation of the cutting edge machine learning algorithms, training models, collaborating with product, engineering, and analytics teams, to build the AI functionalities into each Atlassian products and services. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations. You will be responsible for application of AI/ML to various product problems to improve Atlassian products and actively contribute toAtlassian Intelligence features.
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: $178,200 - $232,650
Zone B: $160,380 - $209,385
Zone C: $147,906 - $193,100
On your first day, we'll expect you to haveBachelor's or Master's degree (preferably a Computer Science degree or equivalent experience).Expertise in Python or Java with and the ability to write performant production-quality code, familiarity with SQL.Knowledge of Spark and cloud data environments is a plus (e.g. AWS, Databricks)Experience building and scaling machine learning models using large amounts of dataExperience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B spaceExperience in developing deep learning-based models and working on LLM-related applicationsExcelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutionsCompensationAt Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. 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: $178,200 - $232,650Zone B: $160,380 - $209,385Zone C: $147,906 - $193,100This role may also be eligible for benefits, bonuses, commissions, and equity.Please visit
Working at AtlassianAtlassians 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. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.Your Future TeamThe mission of Atlassian is to unleash 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. AI/ML is significantly transforming how teams come together to plan, track, and deliver work across software and business teams using our products. We are looking for rockstar Machine learning engineers to come help us to further this mission and help make teams more productive leveraging AI across our product portfolio.
What you'll doAs a Machine Learning engineer, you will work on the development and implementation of the cutting edge machine learning algorithms, training models, collaborating with product, engineering, and analytics teams, to build the AI functionalities into each Atlassian products and services. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations. You will be responsible for application of AI/ML to various product problems to improve Atlassian products and actively contribute toAtlassian Intelligence features.
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: $178,200 - $232,650
Zone B: $160,380 - $209,385
Zone C: $147,906 - $193,100
On your first day, we'll expect you to haveBachelor's or Master's degree (preferably a Computer Science degree or equivalent experience).Expertise in Python or Java with and the ability to write performant production-quality code, familiarity with SQL.Knowledge of Spark and cloud data environments is a plus (e.g. AWS, Databricks)Experience building and scaling machine learning models using large amounts of dataExperience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B spaceExperience in developing deep learning-based models and working on LLM-related applicationsExcelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutionsCompensationAt Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. 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: $178,200 - $232,650Zone B: $160,380 - $209,385Zone C: $147,906 - $193,100This role may also be eligible for benefits, bonuses, commissions, and equity.Please visit
Similar Jobs at Atlassian
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Lead the design and delivery of knowledge graph and machine learning systems that infer personal work context from connected tools. Build graph inference pipelines, schemas, permission-aware APIs, Rovo Chat integrations, and MCP-compatible CLI experiences. Establish evaluation frameworks, improve retrieval and grounding, provide technical direction across teams, mentor engineers, and ensure responsible, privacy-safe AI systems operate reliably at production scale.
Top Skills:
Amazon NeptuneCypherDglGraph DatabasesGraph Neural NetworksGraphxKnowledge GraphsLlm OrchestrationMcpNeo4JOntology DesignPygRagRetrieval-Augmented GenerationSemantic EmbeddingsSparql
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Principal Machine Learning Engineer responsible for setting technical direction and building production-grade AI systems for Confluence. The role spans model evaluation, retrieval, ranking, prompt and workflow design, experimentation, reliability, and customer-facing AI product development. Responsibilities include making architectural decisions, partnering across engineering and product teams, mentoring engineers, identifying model and product failure modes, and delivering scalable AI experiences across content creation, editing, discovery, recommendations, and multimodal interaction.
Top Skills:
Ai Systems InfrastructureArtificial IntelligenceAutomated EvaluationExperimentationMachine LearningMultimodal AiPrompt EngineeringRankingRetrieval
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Lead machine learning architecture and technical direction across multiple quarters while remaining involved in experimentation, quality, and production systems. Work across model post-training, personalization and recommendation, and agentic experiences. Define solutions for ambiguous problems, align cross-functional partners, drive execution, and safely bring ML systems into production.
Top Skills:
Ai AgentsMachine LearningRecommendation Systems
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.

