Cloud Infrastructure Architect

1 week ago

San Francisco, California, United States Waabi Full time

About Us

Waabi is a leading AI company that's revolutionizing the way we think about self-driving technology. Founded by AI pioneer Raquel Urtasun, our team is dedicated to creating innovative solutions that unlock the full potential of AI.

We're seeking a highly skilled Senior Machine Learning Infra Engineer to join our team in Toronto, San Francisco, or Dallas. As a key member of our infrastructure team, you'll play a critical role in designing and implementing scalable and resilient cloud infrastructure optimized for long-term reliability and adaptability.

In this exciting role, you'll have the opportunity to work alongside a talented team of engineers and research scientists using an AI-first approach to enable safe self-driving at scale. You'll collaborate with cross-functional teams to understand the growing need and pain points in cloud usage, propose cloud strategies around compute and data usages for training and simulation workloads, and devise and promote best practices for cloud usages in training and simulation environments.

What We Offer

  • Competitive compensation: $158,000 - $269,000 USD per year (based on experience)
  • Equity incentive awards
  • Annual performance bonus
  • Health and wellness benefits (medical, dental, vision)
  • Unlimited vacation
  • Flexible hours and remote work support
  • Daily drinks, snacks, and catered meals (when in office)
  • Regular team-building activities and social events

About the Role

This is an exciting opportunity to join a world-class team and contribute to the development of cutting-edge AI technology. As a Senior Machine Learning Infra Engineer, you'll be responsible for:

  • Designing and implementing scalable and resilient cloud infrastructure
  • Collaborating with cross-functional teams to identify cloud usage needs and develop cloud strategies
  • Proposing cloud solutions for training and simulation workloads
  • Devise and promote best practices for cloud usages in training and simulation environments

Requirements

  • 5+ years of relevant industry experience
  • BS, MS/PhD in Computer Science or similar technical field of study or equivalent practical experience
  • Deep understanding of cloud compute and data storage for distributed training and inference workloads
  • Familiarity with Python, GO, Rust, or C++ ecosystems
  • Experience working with public cloud platforms (AWS preferred)
  • Experience with infrastructure as code systems (Terraform preferred)
  • Experience in job scheduling and resource allocation
  • Experience with containers and container orchestration (i.e., Docker, ECS, Kubernetes)
  • Experience and high level of comfort working with Linux systems

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