OpenTable · Posted 2w ago
Site Reliability Engineer (AI Platform)
Job relayed by Stapply Data, its source: you apply there.
- Location
- 🇨🇦 Toronto, Canada
- Contract
- Full-time
- Role
- ML engineering
- Source
- Stapply Data
The posting
Join our team as a Site Reliability Engineer II, where you will design, automate, and manage the core container stack and infrastructure for our global business applications. You will be a subject matter expert in Kubernetes, Linux systems, and cloud-native automation, driving the reliability, security, and efficiency of our platform. Collaborate with cross-functional engineering teams, lead infrastructure projects, resolve complex incidents, and build self-service capabilities for application developers. Enjoy generous benefits, including paid vacation, parental leave, and mental health support.
- Design, automate, and manage the core container stack and infrastructure powering global business applications. - Collaborate with cross-functional engineering teams to lead greenfield infrastructure projects, resolve complex incidents, and build self-service capabilities. - Participate in high-impact platform engineering projects and collaborate with globally distributed engineering teams to drive infrastructure standardization.
- 5+ years of hands-on Linux experience (e.g., Ubuntu, CentOS) with expertise in kernel tuning (sysctl), process management (cgroups/namespaces), system calls, and performance optimization - 3+ years of experience using configuration management systems such as Puppet, Chef, Ansible, or SaltStack in production environments - Proven experience building, operating, and troubleshooting bare-metal Kubernetes clusters from the ground up, including control plane, etcd, and CNI plugin management - Proficiency with continuous system automation and scripting in languages such as Go, Python, Ruby, Perl, or Bash - Demonstrated experience responding to live service disruptions, leading root-cause analysis, and operating messaging systems (e.g., Kafka or RabbitMQ) in production - Experience operating, scaling, and monitoring AI/ML or LLM-powered services and workloads in high-concurrency production environments - Hands-on expertise with public cloud providers (AWS, GCE, or Azure) and containerized CI/CD pipelines (e.g., GitHub, Jenkins, CircleCI, Docker) - Experience with distributed key-value stores (e.g., Consul, etcd, Zookeeper, Redis) and enterprise observability/alerting tools (e.g., Prometheus, Sensu) - Familiarity with server virtualization infrastructure (e.g., Proxmox, VMware, Xen, OpenStack) and low-level networking concepts (IPtables/NFTables, routing, load balancing) - Experience developing and maintaining OS-level software packaging (RPM/DEB) and participating in globally distributed software engineering teams