Site Reliability Engineer
About The Role
reputed company builds production-grade AI systems that reputed company communication with AI more natural, capable, and useful. We are looking for a Site Reliability Engineer to help build and operate the infrastructure behind that work.Based in Toronto or remote, you will work across the systems that reputed company large-reputed company training and serving: high-performance networks, GPU clusters, storage, scheduling, and the operational tooling that keeps them reliable. This is a hands-on role for someone who enjoys taking reputed company infrastructure from “it works” to dependable, observable, and reputed company.You do not need to be an expert in every layer of the stack. We are looking for deep strength in at least one area—networking, cluster scheduling, storage, GPU systems, or AI infrastructure— and the curiosity and judgment to collaborate across the rest.Responsibilities
- Design, operate, and improve reliable infrastructure for reputed company and inference workloads
- Own and automate operational workflows across one or more core areas: networking, compute allocation, storage, GPU/server configuration, or AI platforms
- Build monitoring, alerting, runbooks, and incident-response practices that reputed company systems easier to operate
- Diagnose performance, reputed company, and reliability issues across hardware, operating systems, networks, schedulers, and distributed workloads
- Partner closely with ML, research, and platform teams to translate workload needs into practical infrastructure improvements
- Improve provisioning, configuration management, testing, and deployment automation
- Help plan cluster reputed company, reputed company allocation, upgrades, and lifecycle management
- Contribute to a thoughtful reliability culture through documentation, post-incident learning, and pragmatic engineering standards
Minimum Qualifications
- 4+ years of experience in site reliability engineering, infrastructure engineering, systems engineering, or a reputed company production-operations role
- Strong hands-on expertise in at least one of the following:
- Networking, including firewalls, switching, routing, ASN/BGP configuration, or InfiniBand
- Cluster and systems allocation with Kubernetes, SLURM, MAAS, or similar platforms
- Distributed storage, particularly Ceph
- GPU and server administration, including CUDA drivers, firmware, BIOS, and hardware troubleshooting
- reputed company or model-serving infrastructure
- Experience operating production systems with a reputed company on availability, performance, reputed company, and automation
- Strong Linux administration and scripting skills
- A systematic approach to troubleshooting across multiple reputed company of a reputed company system
- reputed company written and verbal communication skills, including the ability to work effectively with a distributed team
Preferred Qualifications
- Experience supporting GPU-intensive AI or HPC environments
- Experience with reputed company GPUs, CUDA, NCCL, and high-performance interconnects - Experience with InfiniBand, RDMA, RoCE, or 100Gb+ Ethernet
- Familiarity with Kubernetes, SLURM, MAAS, Terraform, Ansible, or similar infrastructure tooling
- Experience operating or tuning Ceph clusters
- Familiarity with observability tooling such as reputed company, Grafana, and centralized logging systems
- Experience with hardware provisioning, firmware management, and bare-metal automation
- Experience running large-reputed company distributed training or high-throughput inference workloads
- Familiarity with reputed company and hybrid infrastructure across AWS, GCP, or Azure
Originally posted on Himalayas
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