Develop and deploy scalable machine-learning solutions, particularly deep-learning forecasting models for company top-line metrics. Lead the full ML lifecycle from problem definition and experimentation through production deployment and improvement. Design production-grade architectures, evaluate and improve models, collaborate with cross-functional teams, explain technical concepts to varied audiences, and mentor junior engineers.
Engineering | Mountain View, United States or Remote | Remote, Remote | San Francisco, United States | Austin, United States
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. We are looking for a Senior Machine Learning Engineer to join our Confluence Cloud AI team.
The Confluence Cloud AI team builds and deploys machine-learning solutions that drive revenue generation, expand our active user base, and provide sophisticated forecasting for company top-line metrics. We work across the complete end-to-end machine-learning development lifecycle, from problem definition and experimentation through production deployment and ongoing improvement.
This is a unique opportunity to work in a highly collaborative environment, apply advanced machine-learning techniques, particularly forecasting models, and solve challenging, high-impact problems. You'll collaborate with stakeholders across Growth, GTM, Product, Finance, and Sales while working alongside experienced ML engineers and full-stack engineers.
Working at Atlassian
Atlassians have flexibility in 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, as part of being a distributed-first company.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit
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. We are looking for a Senior Machine Learning Engineer to join our Confluence Cloud AI team.
The Confluence Cloud AI team builds and deploys machine-learning solutions that drive revenue generation, expand our active user base, and provide sophisticated forecasting for company top-line metrics. We work across the complete end-to-end machine-learning development lifecycle, from problem definition and experimentation through production deployment and ongoing improvement.
This is a unique opportunity to work in a highly collaborative environment, apply advanced machine-learning techniques, particularly forecasting models, and solve challenging, high-impact problems. You'll collaborate with stakeholders across Growth, GTM, Product, Finance, and Sales while working alongside experienced ML engineers and full-stack engineers.
Working at Atlassian
Atlassians have flexibility in 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, as part of being a distributed-first company.
- Drive the development and implementation of advanced machine-learning algorithms for business-critical applications.
- Build scalable, reliable, and highly performant forecasting algorithms, including deep-learning-based models, to forecast company top-line metrics at a granular level.
- Lead the end-to-end machine-learning development lifecycle, including problem definition, data preparation, modeling, experimentation, evaluation, deployment, and iteration.
- Design system and model architectures that support production-quality machine-learning solutions.
- Develop rigorous model-evaluation approaches and use data-driven insights to improve model quality and business impact.
- Collaborate with business, engineering, analytics, Growth, GTM, Product, Finance, and Sales teams to translate complex problems into practical solutions.
- Build and improve machine-learning infrastructure and modeling applications that can scale with the needs of the business.
- Explain machine-learning concepts and recommendations clearly to both technical and non-technical audiences.
- Provide technical guidance and mentorship to junior ML engineers.
- Balance high-quality output with business practicality, rapid iteration, and measurable customer and business outcomes.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit
Similar Jobs at Atlassian
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Develop and deploy machine learning and LLM capabilities for agentic search, query understanding, search planning, and retrieval. Build evaluation datasets, improve model behavior through experimentation and fine-tuning, and optimize quality, latency, cost, and reliability. Collaborate across search, product, infrastructure, and AI teams while owning projects through production and mentoring engineers.
Top Skills:
AWSDatabricksInformation RetrievalLarge Language Models (Llms)Machine LearningNatural Language Processing (Nlp)PythonRetrieval-Augmented Generation (Rag)Search RelevanceSpark
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Lead the design, development, deployment, and optimization of production machine learning systems for search, recommendations, personalization, NLP, deep learning, and AI applications. Own projects across the full ML lifecycle, design scalable architectures and evaluation strategies, collaborate with product and engineering teams, translate research into reliable systems, and mentor other engineers.
Top Skills:
SparkAWSData ScienceDatabricksDeep LearningJavaKotlinLarge Language ModelsMachine LearningNatural Language ProcessingPythonSQLTypescript
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Develop and productionize machine learning systems for search, retrieval, ranking, recommendations, conversational experiences, and AI agents. Own projects across the ML lifecycle, build evaluation datasets and benchmarks, conduct offline and online evaluations, analyze model quality, and improve system performance. Design scalable architectures addressing reliability, latency, privacy, and cost. Collaborate across product and engineering teams, communicate technical decisions, mentor engineers, and contribute to ML best practices.
Top Skills:
Agentic SystemsSparkAWSDatabricksDeep LearningEmbeddingsInformation RetrievalJavaKotlinLarge Language ModelsNlpPythonRagRankingRecommendationsSQLTypescript
What you need to know about the Toronto Tech Scene
Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.

