AI-Driven Ecosystem Architect

2 weeks ago

Sydney, New South Wales, Australia beBeeInfrastructure Full time $149,999 - $249,999

Machine Learning Infrastructure Engineer

We are seeking an experienced Machine Learning Infrastructure Engineer to help us build the foundation of our AI-driven ecosystem. As a key member of our infrastructure team, you will be responsible for architecting foundational AI Platform capabilities, making key technical decisions, and leading cross-team initiatives to consolidate and improve dataset and training capabilities.

Key Responsibilities

  • Architecting foundational AI Platform capabilities and making key technical decisions
  • Leading cross-team initiatives to consolidate and improve dataset and training capabilities
  • Building and maintaining scalable distributed data processing and training systems
  • Driving technical strategy discussions and weighing platform stability needs against product velocity requirements
  • Mentoring other engineers and contributing to growing our AI platform engineering capabilities

Requirements

  • Over 5 years of experience building and scaling ML training systems with hands-on experience in distributed training, model lifecycle management, and large-scale data processing
  • Proven track record of designing and implementing foundational AI/ML infrastructure that supports multiple teams and use cases
  • Experience setting technical direction, making architectural decisions, and influencing engineering practices across organizations
  • Strong understanding of distributed computing, container orchestration (Kubernetes), and cloud infrastructure
  • Fluent in Python with deep knowledge of ML frameworks and modern tools
  • Strong understanding of generative AI systems, including LLMs, multimodal models, and foundation model fine-tuning

About the Team

Our infrastructure team is responsible for delivering capabilities and solutions that support ML and AI initiatives, from early ideation and prototyping through to scaling to meet the needs of millions of users in production.

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