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Remote Hpc Engineer Jobs in Toronto, ON (NOW HIRING)

Site Reliability Engineer

Toronto, ON · On-site +1

CA$125K - CA$250K/yr

Based in Toronto or remote, you will work across the systems that enable large-scale AI training ... Experience supporting GPU-intensive AI or HPC environments * Experience with NVIDIA GPUs, CUDA ...

Were a nimble, cross-functional team of scientists, engineers, designers, and product thinkers ... Familiarity with cloud and/or HPC computing environments and reproducibility best practices. * A ...

We're a nimble, cross-functional team of scientists, engineers, designers, and product thinkers ... Familiarity with cloud and/or HPC computing environments and reproducibility best practices. * A ...

Remote Hpc Engineer information

What skills and qualifications are needed to be a remote HPC engineer?

To thrive as a Remote HPC Engineer, you need a solid background in computer science or engineering, expertise in high-performance computing architectures, and experience with parallel programming. Familiarity with HPC job schedulers (like Slurm), Linux systems, distributed storage, and relevant certifications (such as CompTIA Linux+ or HPC-specific credentials) are commonly required. Strong problem-solving abilities, effective communication, and self-motivation are vital soft skills for addressing complex technical challenges remotely. These competencies ensure efficient system performance, seamless collaboration, and successful support of computational research or enterprise workloads.

What is a remote HPC engineer?

Remote HPC (High Performance Computing) Engineers are professionals who design, implement, and manage high-performance computing systems, typically from a remote location. They work with powerful computer clusters and supercomputers to support complex computations in fields like scientific research, engineering, and data analysis. Their responsibilities include configuring hardware and software, optimizing system performance, troubleshooting issues, and ensuring the security and reliability of HPC resources. By working remotely, these engineers can support organizations and research teams around the world without needing to be physically present at the data center.

What is the difference between Remote Hpc Engineer vs Remote Cloud Engineer?

AspectRemote Hpc EngineerRemote Cloud Engineer
Required CredentialsBachelor's in Computer Science or related, certifications like HPC or LinuxBachelor's in Computer Science or related, cloud certifications (AWS, Azure)
Work EnvironmentHigh-performance computing clusters, research labs, data centersCloud platforms, virtual environments, cloud service providers
Employer & Industry UsageResearch institutions, scientific organizations, tech companiesTech firms, startups, enterprises using cloud infrastructure
Common Search & ComparisonYesYes

The main difference between a Remote Hpc Engineer and a Remote Cloud Engineer lies in their focus areas. Hpc Engineers specialize in high-performance computing systems used for scientific and research purposes, while Cloud Engineers focus on designing and managing cloud-based infrastructure. Both roles require technical expertise and certifications, but their work environments and industry applications differ significantly.

How do remote HPC engineers collaborate with on-site teams to manage high-performance computing clusters?

Remote HPC Engineers often rely on robust communication tools and version control systems to coordinate with on-site system administrators, researchers, and IT staff. They participate in regular virtual meetings to discuss cluster performance, resolve technical issues, and plan for upgrades or maintenance. Secure remote access protocols allow engineers to monitor, troubleshoot, and configure systems from afar, but effective collaboration also depends on clear documentation and periodic knowledge sharing sessions. Building strong relationships with on-site personnel helps ensure smooth operations and prompt resolution of any hardware or software challenges.
What are the most commonly searched types of Hpc Engineer jobs in Toronto, ON? The most popular types of Hpc Engineer jobs in Toronto, ON are:
What are popular job titles related to Remote Hpc Engineer jobs in Toronto, ON? For Remote Hpc Engineer jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Remote Hpc Engineer jobs in Toronto, ON look for? The top searched job categories for Remote Hpc Engineer jobs in Toronto, ON are:
Infographic showing various Remote Hpc Engineer job openings in Toronto, ON as of June 2026, with employment types broken down into 58% Full Time, 32% Part Time, and 10% Contract. Highlights an 48% Physical, 6% Hybrid, and 46% Remote job distribution.

Site Reliability Engineer

Boson AI

Toronto, ON • On-site, Remote

CA$125K - CA$250K/yr

Full-time

Posted 24 days ago


Job description

About The Role
 
Boson AI builds production-grade AI systems that make 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 enable large-scale AI 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 complex infrastructure from "it works" to dependable, observable, and scalable.
 
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 AI training 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 make systems easier to operate
  • Diagnose performance, capacity, 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 growth, capacity 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 related 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
    • AI training or model-serving infrastructure
  • 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, including the ability to work effectively with a distributed team
Preferred Qualifications
  • Experience supporting GPU-intensive AI or HPC environments
  • Experience with NVIDIA 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 Prometheus, Grafana, and centralized logging systems
  • Experience with hardware provisioning, firmware management, and bare-metal automation
  • Experience running large-scale distributed training or high-throughput inference workloads
  • Familiarity with cloud and hybrid infrastructure across AWS, GCP, or Azure
$125,000 - $250,000 a year
Boson AI is building AI systems for real-world, business-critical use. If you enjoy solving difficult infrastructure problems and want your work to directly enable the next generation of AI products, we'd love to hear from you.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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