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Site Reliability Engineer

4 days, 19 hours ago
Canada
Full-time
Mid Level
Site Reliability Engineer (SRE)
DevOps and Infrastructure
Ansible AWS Azure GCP Grafana Kubernetes Linux Prometheus Terraform
Apply Now
Boson AI

Boson AI

Boson AI develops advanced voice agents that utilize foundation models and continuous learning to facilitate seamless and engaging communication between humans and AI, tailored specifically to various business domains.

Internet Software & Services
Founded 2023
View All Jobs

Description

  • Design, operate, and improve reliable infrastructure for AI training and inference workloads.
  • Own and automate operational workflows across networking, compute allocation, storage, GPU/server configuration, or AI platforms.
  • Build monitoring, alerting, runbooks, and incident-response practices to improve operability.
  • Diagnose performance, capacity, and reliability issues across hardware, operating systems, networks, schedulers, and distributed workloads.
  • Partner with ML, research, and platform teams to turn workload needs into infrastructure improvements.
  • Improve provisioning, configuration management, testing, and deployment automation.
  • Plan cluster growth, capacity allocation, upgrades, and lifecycle management.
  • Contribute to reliability standards through documentation and post-incident learning.

Requirements

  • 4+ years of experience in site reliability engineering, infrastructure engineering, systems engineering, or a related production-operations role.
  • Strong hands-on expertise in at least one of the following: networking, cluster and systems allocation, distributed storage, GPU and server administration, or AI training/model-serving infrastructure.
  • Experience with networking topics such as firewalls, switching, routing, ASN/BGP configuration, or InfiniBand.
  • Experience with Kubernetes, SLURM, MAAS, or similar cluster management platforms.
  • Experience with distributed storage, particularly Ceph.
  • Experience with GPU and server administration, including CUDA drivers, firmware, BIOS, and hardware troubleshooting.
  • Experience operating production systems with a focus on availability, performance, security, and automation.
  • Strong Linux administration and scripting skills.
  • A systematic approach to troubleshooting across multiple layers of a complex system.
  • Clear written and verbal communication skills and the ability to work effectively with a distributed team.
  • Experience supporting GPU-intensive AI or HPC environments (preferred).
  • Experience with NVIDIA GPUs, CUDA, NCCL, InfiniBand, RDMA, RoCE, or 100Gb+ Ethernet (preferred).
  • Familiarity with Kubernetes, SLURM, MAAS, Terraform, Ansible, or similar infrastructure tooling (preferred).
  • Experience operating or tuning Ceph clusters (preferred).
  • Familiarity with observability tooling such as Prometheus, Grafana, and centralized logging systems (preferred).
  • Experience with hardware provisioning, firmware management, and bare-metal automation (preferred).
  • Experience running large-scale distributed training or high-throughput inference workloads (preferred).
  • Familiarity with cloud and hybrid infrastructure across AWS, GCP, or Azure (preferred).

Interested in this position?

Apply directly on the company website

Apply Now

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