Senior Machine Learning Systems Engineer

About the Position

As a Senior Machine Learning Systems Engineer on the AI & ML Platform team at Atlassian, 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.

Responsibilities

• 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.

Requirements

• 6+ years of general software engineering experience with 2+ years in building Machine Learning and AI infra/Platform/Systems.
• Comprehensive ML lifecycle expertise: Proven experience developing, deploying, and maintaining end-to-end ML systems, from data engineering to model serving and monitoring.
• 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: Good proficiency in Python and familiarity with ML frameworks like PyTorch, TensorFlow, or JAX. Bonus if you have worked with other languages like Go, Java, or Scala.
• MLOps and automation: Some experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models.

Nice to Have

• 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.

We Offer

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 the Company

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.