Atlassian

Machine Learning Platform Engineer

Atlassian Sydney, New South Wales, Australia

Software Development · 10,001+ employees

Aug 01
Remote machine-learning Mid (2-5 yrs) Other Australia
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About the role

You will develop and refine the core infrastructure that empowers engineers and data scientists to create, train, deploy, and manage machine learning models. You will also collaborate with product teams to solve complex challenges and lead projects from technical design to launch.

What they look for

Machine Learning Python PyTorch TensorFlow JAX MLOps CI/CD Distributed systems Cloud infrastructure AWS GCP Azure Spark Ray Dask Large Language Models

Requirements

Candidates must have at least 2 years of experience in building machine learning and AI infrastructure. Proficiency in Python, ML frameworks, and experience with MLOps, CI/CD pipelines, and large-scale system design is required.

Benefits

Health and wellbeing resources Paid volunteer days Equity Bonuses Commissions

Full description

Overview

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.

Responsibilities

As an ML System Engineer on the AI & ML Platform team, you will play a pivotal role in developing and refining the core infrastructure that empowers all Atlassian software engineers, ML engineers, and data scientists to create, train, evaluate, deploy, and manage Machine Learning models and pipelines.

You will collaborate closely with product teams, such as Jira and Confluence, to solve their specific challenges in building ML solutions. This may involve curating high-quality ML datasets, fine-tuning open-sourced Large Language Models (LLMs), or accessing proprietary LLMs. Your expertise in both ML and software development expertise will be instrumental in overcoming challenging problems and navigating complex infrastructure and architectural issues.

This position offers you the chance to lead projects from the technical design phase all the way to launch. You will partner with various teams and internal stakeholders to achieve impactful results.

In this role, you'll get the chance to:

  • Collaborate with your teammates to solve complex problems, from technical design to launch.
  • Deliver cutting-edge solutions that are used by other Atlassian teams and products to build AI features that reach millions of customers.
  • Deliver code reviews, documentation & bug fixes within a strong engineering culture
  • Partner across engineering teams to take on company-wide initiatives spanning multiple projects.
  • Mentor junior members of the team.

On your first day, we’ll expect you to have

  • 2+ years of experience in building Machine Learning and AI infra/platform/system
  • Comprehensive ML lifecycle expertise: proven experience developing, deploying, and maintaining end-to-end ML systems, from data engineering to model serving and monitoring.
  • MLOps and automation: Deep experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models.

Compensation

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.

This role may also be eligible for benefits, bonuses, commissions, and equity.

Qualifications

Qualifications

  • Large-scale system design: Extensive experience designing and building scalable, fault-tolerant, and high-performance distributed systems for machine learning.
  • Proficiency with frameworks and languages: Expert-level proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX. Familiarity with other languages like Go, Java, or Scala is also beneficial.
  • Cloud infrastructure: Hands-on expertise with major cloud platforms such as AWS, GCP, or Azure, including their specific AI/ML services and compute resources like GPUs.
  • Big data processing: Experience with distributed computing frameworks for large-scale data processing, such as Spark, Ray, or Dask.
  • Performance optimization: A demonstrated ability to diagnose and solve complex performance and optimization problems for ML models and infrastructure.
  • Generative AI systems: Experience with GenAI frameworks and tools, including developing and fine-tuning large language models (LLMs) and building retrieval-augmented generation (RAG) systems.

Benefits & Perks

Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.

About Atlassian

At Atlassian, we're motivated by a common goal: to unleash the 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.

We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.

To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.

To learn more about our culture and hiring process, visit go.atlassian.com/crh.

In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.

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