Senior Machine Learning System Engineer

Atlassian • San Francisco, CA

163d • $168,300 - $264,375

About The Position

As a Senior Software Engineer in the Central AI team, you will build and maintain the core infrastructure to allow machine learning engineers and data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines. You will use your software development expertise to solve difficult problems, tackling complex infrastructure and architecture challenges. You will have the opportunity to lead other engineers to drive involved projects from technical design to launch. You will also collaborate with other teams and internal customers to set expectations, gather input and communicate results. The Central AI org is part of the larger Atlassian Intelligence program. Its purpose is to accelerate AI innovation across all our products and platform, provide cohesive AI experiences and setup up an Atlassian AI infrastructure for the future. While it's anticipated that the majority of AI-driven initiatives will be developed and executed by federated product teams within Atlassian, the role of Central AI is pivotal to this process. Central AI is tasked with constructing the underlying infrastructure and capacities, which are crucial for the seamless integration and optimal functionality of AI across various departments. By doing so, Central AI ensures that different teams within the organization do not work in silos but have access to a unified foundation that promotes efficiency and collaboration. Additionally, Central AI is responsible for developing some of the core shared experiences typical in the AI domain, such as search, knowledge discovery and conversation.

Requirements

• 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.

Nice To Haves

• Expert-level with search platform, deep learning training/inference platform.
• Experience with Databricks.
• Experience with scaling and deploying Machine Learning models.

Responsibilities

• Build and maintain core infrastructure for machine learning models and pipelines.
• Solve complex infrastructure and architecture challenges.
• Lead other engineers on technical design and project launch.
• Collaborate with teams and internal customers to set expectations and communicate results.

Benefits

• Health and wellbeing resources.
• Paid volunteer days.
• Equitable and competitive compensation programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees