Site Reliability Engineer

We are looking for a Site Reliability Engineer to design the systems and processes that our engineers use to manage and deploy their software into production. We’re excited about the opportunity to make a social impact and change an industry through data science and deep learning. We are looking for someone with experience building and managing rock-solid infrastructure who can help foster a culture of DevOps.

This is an exciting opportunity to part of a startup that is applying deep learning to a real-world problem at global scale. We’re always looking for leaders and there is room to grow for the right person to take increasing responsibility working as part of a small and dynamic team.


Melbourne, Tokyo, San Francisco (remote work possible)


  • Automate the process of provisioning and manage cloud infrastructure for our web application and machine learning needs, balancing performance with cost effectiveness

  • Work directly with our CTO and development team to define and evolve our architecture.

  • Design systems and processes for our engineers to deploy software into production.

  • Minimize risk of reliability related failure outcomes as pertaining to durability, availability, performance, and correctness

  • Monitor reliability performance of our web application and communicate this information to stakeholders

  • Foster and promote operational awareness within the engineering team.

  • Evolve and tune our CI/CD pipelines

Minimum Qualifications and Education Requirements:

  • BSc/BSc/BEng degree in computer science or equivalent

  • Experience building and operating large-scale production systems

  • A track record of working collaboratively in a rapidly moving engineering team

  • Experience using Docker in production

  • A passion for repeatability and eliminating human effort through software automation

  • Proficiency in shell scripting

  • Proficiency in Linux admin

Preferred Qualifications:

  • MSc/MEng degree in computer science, mathematics, machine learning or equivalent

  • Experience deploying machine learning services in production

  • Passion for AI and excitement about new developments

  • Contributions to open source projects

  • Experience with Kubernetes in production

  • Good understanding of security best practices

    To apply, please contact us at with your CV.