Machine Learning Systems Engineer
Atlassian
Machine Learning Systems Engineer
Job Description
Machine Learning Systems Engineer
📋 Job Overview
As a Machine Learning Systems Engineer at Atlassian, you will build and scale core infrastructure to support the development, training, evaluation, deployment, and operation of Machine Learning models and pipelines. You will also lead projects from technical design to launch, collaborate with other teams, and mentor junior members. This role focuses on creating user-friendly and reliable tools to democratize Machine Learning across Atlassian's products and ecosystem.
📍 Location: San Francisco, United States
🏢 Category: Engineering
📅 Posted: 2025-11-15 12:17 AM
🎯 Key Responsibilities
- Build and scale core infrastructure for developing, training, evaluating, deploying, and operating Machine Learning models and pipelines
- Build systems for product teams like Jira & Confluence to provide access to curated LLMs
- Solve difficult problems, tackling infrastructure and architecture challenges
- Lead engineers to drive involved projects from technical design to launch
- Collaborate with other teams and internal customers to set expectations, gather input and communicate results
- Regularly tackle complex problems in the team, from technical design to launch
- Routinely tackle complex architecture challenges and define coding standards & patterns for the team
- Lead the team through times of ambiguity, help them adapt and deliver positive impact
- Mentor junior members on the team
✅ Required Qualifications
- Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin)
- Understanding and experience with Machine Learning project lifecycle and tools
- Understanding of LLMs, best deployment practices and inference optimisation
- Experience in building and implementing high-performance RESTful micro-services
- Experience building and operating large scale distributed systems using Amazon Web Services (Sagemaker, S3, Cloud Formation, AWS Security and Networking)
- Experience with Continuous Delivery and Continuous Integration
🛠️ Required Skills
- Java
- Kotlin
- AWS
- Sagemaker
- S3
- Cloud Formation
- AWS Security
- AWS Networking
- Continuous Delivery
- Continuous Integration
- RESTful micro-services
- LLMs
- Machine Learning
- Leadership
- Collaboration
- Mentoring
- Problem-solving
- Architecture design
- Technical design
🎁 Benefits & Perks
- Health coverage
- Paid volunteer days
- Wellness resources
Locations
- San Francisco, United States
Salary
Estimated Salary Rangemedium confidence
150,000 - 220,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Javaintermediate
- Kotlinintermediate
- AWSintermediate
- Sagemakerintermediate
- S3intermediate
- Cloud Formationintermediate
- AWS Securityintermediate
- AWS Networkingintermediate
- Continuous Deliveryintermediate
- Continuous Integrationintermediate
- RESTful micro-servicesintermediate
- LLMsintermediate
- Machine Learningintermediate
- Leadershipintermediate
- Collaborationintermediate
- Mentoringintermediate
- Problem-solvingintermediate
- Architecture designintermediate
- Technical designintermediate
Required Qualifications
- Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin) (experience)
- Understanding and experience with Machine Learning project lifecycle and tools (experience)
- Understanding of LLMs, best deployment practices and inference optimisation (experience)
- Experience in building and implementing high-performance RESTful micro-services (experience)
- Experience building and operating large scale distributed systems using Amazon Web Services (Sagemaker, S3, Cloud Formation, AWS Security and Networking) (experience)
- Experience with Continuous Delivery and Continuous Integration (experience)
Responsibilities
- Build and scale core infrastructure for developing, training, evaluating, deploying, and operating Machine Learning models and pipelines
- Build systems for product teams like Jira & Confluence to provide access to curated LLMs
- Solve difficult problems, tackling infrastructure and architecture challenges
- Lead engineers to drive involved projects from technical design to launch
- Collaborate with other teams and internal customers to set expectations, gather input and communicate results
- Regularly tackle complex problems in the team, from technical design to launch
- Routinely tackle complex architecture challenges and define coding standards & patterns for the team
- Lead the team through times of ambiguity, help them adapt and deliver positive impact
- Mentor junior members on the team
Benefits
- general: Health coverage
- general: Paid volunteer days
- general: Wellness resources
Tags & Categories
Machine Learning Systems Engineer
Atlassian
Machine Learning Systems Engineer
Job Description
Machine Learning Systems Engineer
📋 Job Overview
As a Machine Learning Systems Engineer at Atlassian, you will build and scale core infrastructure to support the development, training, evaluation, deployment, and operation of Machine Learning models and pipelines. You will also lead projects from technical design to launch, collaborate with other teams, and mentor junior members. This role focuses on creating user-friendly and reliable tools to democratize Machine Learning across Atlassian's products and ecosystem.
📍 Location: San Francisco, United States
🏢 Category: Engineering
📅 Posted: 2025-11-15 12:17 AM
🎯 Key Responsibilities
- Build and scale core infrastructure for developing, training, evaluating, deploying, and operating Machine Learning models and pipelines
- Build systems for product teams like Jira & Confluence to provide access to curated LLMs
- Solve difficult problems, tackling infrastructure and architecture challenges
- Lead engineers to drive involved projects from technical design to launch
- Collaborate with other teams and internal customers to set expectations, gather input and communicate results
- Regularly tackle complex problems in the team, from technical design to launch
- Routinely tackle complex architecture challenges and define coding standards & patterns for the team
- Lead the team through times of ambiguity, help them adapt and deliver positive impact
- Mentor junior members on the team
✅ Required Qualifications
- Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin)
- Understanding and experience with Machine Learning project lifecycle and tools
- Understanding of LLMs, best deployment practices and inference optimisation
- Experience in building and implementing high-performance RESTful micro-services
- Experience building and operating large scale distributed systems using Amazon Web Services (Sagemaker, S3, Cloud Formation, AWS Security and Networking)
- Experience with Continuous Delivery and Continuous Integration
🛠️ Required Skills
- Java
- Kotlin
- AWS
- Sagemaker
- S3
- Cloud Formation
- AWS Security
- AWS Networking
- Continuous Delivery
- Continuous Integration
- RESTful micro-services
- LLMs
- Machine Learning
- Leadership
- Collaboration
- Mentoring
- Problem-solving
- Architecture design
- Technical design
🎁 Benefits & Perks
- Health coverage
- Paid volunteer days
- Wellness resources
Locations
- San Francisco, United States
Salary
Estimated Salary Rangemedium confidence
150,000 - 220,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Javaintermediate
- Kotlinintermediate
- AWSintermediate
- Sagemakerintermediate
- S3intermediate
- Cloud Formationintermediate
- AWS Securityintermediate
- AWS Networkingintermediate
- Continuous Deliveryintermediate
- Continuous Integrationintermediate
- RESTful micro-servicesintermediate
- LLMsintermediate
- Machine Learningintermediate
- Leadershipintermediate
- Collaborationintermediate
- Mentoringintermediate
- Problem-solvingintermediate
- Architecture designintermediate
- Technical designintermediate
Required Qualifications
- Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin) (experience)
- Understanding and experience with Machine Learning project lifecycle and tools (experience)
- Understanding of LLMs, best deployment practices and inference optimisation (experience)
- Experience in building and implementing high-performance RESTful micro-services (experience)
- Experience building and operating large scale distributed systems using Amazon Web Services (Sagemaker, S3, Cloud Formation, AWS Security and Networking) (experience)
- Experience with Continuous Delivery and Continuous Integration (experience)
Responsibilities
- Build and scale core infrastructure for developing, training, evaluating, deploying, and operating Machine Learning models and pipelines
- Build systems for product teams like Jira & Confluence to provide access to curated LLMs
- Solve difficult problems, tackling infrastructure and architecture challenges
- Lead engineers to drive involved projects from technical design to launch
- Collaborate with other teams and internal customers to set expectations, gather input and communicate results
- Regularly tackle complex problems in the team, from technical design to launch
- Routinely tackle complex architecture challenges and define coding standards & patterns for the team
- Lead the team through times of ambiguity, help them adapt and deliver positive impact
- Mentor junior members on the team
Benefits
- general: Health coverage
- general: Paid volunteer days
- general: Wellness resources
Tags & Categories