AIML - Site Reliability Engineer (SRE), Siri Knowledge Platforms

AIML - Site Reliability Engineer (SRE), Siri Knowledge Platforms

London, England, United Kingdom Machine Learning and AI

Description

As an SRE in the AI/ML organisation within Apple, you will be directly responsible for the infrastructure that powers Siri, search, and other high-impact user-facing solutions running on millions of Apple devices worldwide.We strive to improve the stability, security, efficiency, and scalability of a 24/7 global service. We have on-call rotations-working in a geographically distributed SRE teams for follow-the-sun support. Your strong troubleshooting ability will be used daily to isolate issues and resolve the root cause through investigative analysis. The role also requires building and maintaining accurate, up-to-date documentation reflecting configuration, providing code reviews, and mentoring new team members.An ideal candidate is an independent problem-solver who is focused and capable of exhibiting deftness to handle multiple simultaneous contending priorities and deliver solutions in a timely manner.

Minimum Qualifications

• A strong sense of ownership and integrity demonstrated through clear communication and collaboration.
• Sophisticated knowledge of one or more of the following: Kubernetes, containerisation systems, and/or public cloud infrastructure (AWS, GCP).
• Proficiency in Go, Python, or similar language to automate tasks.
• Hands-on experience handling large numbers of diverse systems with configuration management or software delivery platforms (such as Puppet, Chef, Ansible, and Spinnaker).

Preferred Qualifications

• Working knowledge of multi-tier applications and their dependencies including load balancing, TCP/IP networking, web services, LDAP and DNS.
• Proficiency with web server administration including Apache and Nginx.
• Knowledge of database design, support and administration including Postgres, MySQL, and HBase.
• Network administration and troubleshooting.
• Good interpersonal skills shown through previous projects or assignments.