Site Reliability Engineer
At amplified ai we are a small, fast-moving international team using cutting edge AI to make patents simpler and fairer. And in doing so change how the world innovates.
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.
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
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 firstname.lastname@example.org with your CV.