Senior Machine Learning System Engineer
About The Position
Atlassian is seeking a Senior Machine Learning System Engineer to join their Central AI Org, specifically the AI & ML Platform Team. This role is crucial in developing and refining the core infrastructure that empowers Atlassian software engineers, ML engineers, and data scientists to create, train, evaluate, deploy, and manage Machine Learning models and pipelines. The engineer will collaborate with product teams like Jira and Confluence to address their ML challenges, potentially involving data curation, fine-tuning LLMs, or accessing proprietary LLMs. The position offers the opportunity to lead projects from technical design to launch, partnering with various teams and stakeholders. The Central AI Org focuses on driving AI innovation across Atlassian products, establishing robust AI infrastructure, and creating centralized Search, Q&A, and Conversational AI systems. The AI & ML Platform Team aims to democratize AI and ML for Atlassian's ecosystem by building productive and reliable tools for AI/ML development, deployment, measurement, and operation, integrating seamlessly with platforms like the Atlassian Data Platform while adhering to security and data usage policies.
Requirements
- 5+ 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.
- Large-scale system design: Extensive experience designing and building scalable, fault-tolerant, and high-performance distributed systems for machine learning.
- MLOps and automation: Deep experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models.
Nice To Haves
- 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.
- Hands-on expertise with major cloud platforms such as AWS, GCP, or Azure, including their specific AI/ML services and compute resources like GPUs.
- Experience with distributed computing frameworks for large-scale data processing, such as Spark, Ray, or Dask.
- A demonstrated ability to diagnose and solve complex performance and optimization problems for ML models and infrastructure.
- Experience with GenAI frameworks and tools, including developing and fine-tuning large language models (LLMs) and building retrieval-augmented generation (RAG) systems.
Responsibilities
- Develop horizontal AI capabilities and infrastructure that can be leveraged across all products.
- Establish a centralized Search, Q&A, and Conversational AI system that integrates seamlessly with all Atlassian products.
- Explore the integration of Atlassian products with AI solutions beyond the Atlassian ecosystem.
- Build the foundations to democratize AI and Machine Learning for Atlassian’s teams, customers, and ecosystem.
- Build productive and reliable tools that empower Atlassian teams to harness the power of AI.
- Facilitate the development, deployment, measurement, and operation of AI & ML experiences.
- Integrate tools seamlessly with other Atlassian platforms, including the Atlassian Data Platform.
- Develop and refine 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.
- Collaborate closely with product teams, such as Jira and Confluence, to solve their specific challenges in building ML solutions.
- Curate high-quality ML datasets, fine-tune open-sourced Large Language Models (LLMs), or access proprietary LLMs.
- Lead projects from the technical design phase all the way to launch.
- Partner with various teams and internal stakeholders to achieve impactful results.
- Collaborate with 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.
Benefits
- health and wellbeing resources
- paid volunteer days
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
