Principal Machine Learning System Engineer
Atlassian
Principal Machine Learning System Engineer
Job Description
Principal Machine Learning System Engineer
📋 Job Overview
As a Principal Machine Learning System Engineer at Atlassian, you will build and maintain core infrastructure to support machine learning engineers and data scientists in developing, training, evaluating, deploying, and operating ML models and pipelines. You will tackle complex infrastructure and architecture challenges, lead projects from design to launch, and collaborate with various teams to set expectations and communicate results.
📍 Location: San Francisco, United States
🏢 Category: Engineering
📅 Posted: 2025-11-15 12:16 AM
🎯 Key Responsibilities
- Build and maintain core infrastructure for machine learning engineers and data scientists
- Solve difficult problems and tackle complex infrastructure and architecture challenges
- Lead other engineers to drive projects from technical design to launch
- Collaborate with other teams and internal customers to set expectations, gather input, and communicate results
✅ Required Qualifications
- 5+ years of experience as a software developer
- Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin and Python)
- Experience with Continuous Delivery and Continuous Integration
- Experience building and operating large scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking)
- Experience with distributed large-scale data processing (preferably Apache Spark)
- Basic understanding of Machine Learning projects lifecycle
⭐ Preferred Qualifications
- Expert-level with search platform
- Deep learning training/inference platform experience
- Experience with Databricks
- Experience with scaling and deploying Machine Learning models
🛠️ Required Skills
- Software development
- Java
- Kotlin
- Python
- Continuous Delivery
- Continuous Integration
- Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking)
- Apache Spark
- Machine Learning
- Leadership
- Collaboration
- Communication
🎁 Benefits & Perks
- Health coverage
- Paid volunteer days
- Wellness resources
Locations
- San Francisco, United States
Salary
Estimated Salary Rangemedium confidence
200,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Software developmentintermediate
- Javaintermediate
- Kotlinintermediate
- Pythonintermediate
- Continuous Deliveryintermediate
- Continuous Integrationintermediate
- Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking)intermediate
- Apache Sparkintermediate
- Machine Learningintermediate
- Leadershipintermediate
- Collaborationintermediate
- Communicationintermediate
Required Qualifications
- 5+ years of experience as a software developer (experience)
- Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin and Python) (experience)
- Experience with Continuous Delivery and Continuous Integration (experience)
- Experience building and operating large scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking) (experience)
- Experience with distributed large-scale data processing (preferably Apache Spark) (experience)
- Basic understanding of Machine Learning projects lifecycle (experience)
Preferred Qualifications
- Expert-level with search platform (experience)
- Deep learning training/inference platform experience (experience)
- Experience with Databricks (experience)
- Experience with scaling and deploying Machine Learning models (experience)
Responsibilities
- Build and maintain core infrastructure for machine learning engineers and data scientists
- Solve difficult problems and tackle complex infrastructure and architecture challenges
- Lead other engineers to drive projects from technical design to launch
- Collaborate with other teams and internal customers to set expectations, gather input, and communicate results
Benefits
- general: Health coverage
- general: Paid volunteer days
- general: Wellness resources
Tags & Categories
Principal Machine Learning System Engineer
Atlassian
Principal Machine Learning System Engineer
Job Description
Principal Machine Learning System Engineer
📋 Job Overview
As a Principal Machine Learning System Engineer at Atlassian, you will build and maintain core infrastructure to support machine learning engineers and data scientists in developing, training, evaluating, deploying, and operating ML models and pipelines. You will tackle complex infrastructure and architecture challenges, lead projects from design to launch, and collaborate with various teams to set expectations and communicate results.
📍 Location: San Francisco, United States
🏢 Category: Engineering
📅 Posted: 2025-11-15 12:16 AM
🎯 Key Responsibilities
- Build and maintain core infrastructure for machine learning engineers and data scientists
- Solve difficult problems and tackle complex infrastructure and architecture challenges
- Lead other engineers to drive projects from technical design to launch
- Collaborate with other teams and internal customers to set expectations, gather input, and communicate results
✅ Required Qualifications
- 5+ years of experience as a software developer
- Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin and Python)
- Experience with Continuous Delivery and Continuous Integration
- Experience building and operating large scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking)
- Experience with distributed large-scale data processing (preferably Apache Spark)
- Basic understanding of Machine Learning projects lifecycle
⭐ Preferred Qualifications
- Expert-level with search platform
- Deep learning training/inference platform experience
- Experience with Databricks
- Experience with scaling and deploying Machine Learning models
🛠️ Required Skills
- Software development
- Java
- Kotlin
- Python
- Continuous Delivery
- Continuous Integration
- Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking)
- Apache Spark
- Machine Learning
- Leadership
- Collaboration
- Communication
🎁 Benefits & Perks
- Health coverage
- Paid volunteer days
- Wellness resources
Locations
- San Francisco, United States
Salary
Estimated Salary Rangemedium confidence
200,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Software developmentintermediate
- Javaintermediate
- Kotlinintermediate
- Pythonintermediate
- Continuous Deliveryintermediate
- Continuous Integrationintermediate
- Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking)intermediate
- Apache Sparkintermediate
- Machine Learningintermediate
- Leadershipintermediate
- Collaborationintermediate
- Communicationintermediate
Required Qualifications
- 5+ years of experience as a software developer (experience)
- Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin and Python) (experience)
- Experience with Continuous Delivery and Continuous Integration (experience)
- Experience building and operating large scale distributed systems using Amazon Web Services (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking) (experience)
- Experience with distributed large-scale data processing (preferably Apache Spark) (experience)
- Basic understanding of Machine Learning projects lifecycle (experience)
Preferred Qualifications
- Expert-level with search platform (experience)
- Deep learning training/inference platform experience (experience)
- Experience with Databricks (experience)
- Experience with scaling and deploying Machine Learning models (experience)
Responsibilities
- Build and maintain core infrastructure for machine learning engineers and data scientists
- Solve difficult problems and tackle complex infrastructure and architecture challenges
- Lead other engineers to drive projects from technical design to launch
- Collaborate with other teams and internal customers to set expectations, gather input, and communicate results
Benefits
- general: Health coverage
- general: Paid volunteer days
- general: Wellness resources
Tags & Categories