AI Infrastructure Engineering Lead

4 days ago

Brisbane, Queensland, Australia beBeeArchitect Full time $180,000 - $240,000
**Chief AI Infrastructure Architect Role Summary:**
  • Technical leader for AI infrastructure engineering with expertise in designing and implementing foundational AI/ML infrastructure.

As a seasoned technical leader, we are seeking an individual to head our AI infrastructure engineering efforts. This role involves building scalable and efficient AI platforms focusing on cost efficiency and developer experience.

The ideal candidate will have hands-on experience in distributed training, model lifecycle management, and large-scale data processing, as well as a strong understanding of cloud infrastructure, container orchestration, and ML frameworks.

Key Responsibilities:
  • Designing and implementing distributed data processing and training systems that meet the needs of multiple teams and use cases.
  • Leading cross-functional initiatives to improve dataset and training capabilities, working closely with stakeholders across engineering and research teams.
  • Building and maintaining a robust and secure AI platform, making key technical decisions that impact model training and deployment.
  • Driving technical strategy discussions, weighing platform stability against product velocity requirements.
  • Mentoring and growing other engineers, contributing to the growth of our AI platform engineering capabilities.
  • Solving complex technical challenges spanning multiple parts of the ML stack, staying up-to-date with industry trends and advancements.

**Requirements:**

  • More than 5 years of experience in building and scaling ML training systems, including 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 (AWS).
  • Fluent in Python with deep knowledge of ML frameworks (PyTorch, TensorFlow) and modern tools (W&B, Ray, Anyscale).
  • Strong understanding of generative AI systems, including LLMs, multimodal models, and foundation model fine-tuning.

**What We Offer:**

  • A dynamic and collaborative work environment that fosters growth and innovation.
  • Ongoing opportunities for professional development and skill-building.
  • The chance to make meaningful contributions to cutting-edge AI projects and products.
  • Opportunities to collaborate with talented engineers and researchers from diverse backgrounds.
  • Flexible work arrangements that support work-life balance.
  • Competitive compensation and benefits package.
  • Recognition and rewards for outstanding performance and contributions.

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