High Performance Computing Engineer

Boson AI; Toronto; On-site; CAD 150,000 - 250,000; Full time

Job summary

Boson AI is seeking a Senior High Performance Computing Engineer to manage GPU clusters and related infrastructure in Toronto. The role involves a range of responsibilities including configuring systems and managing on-premises Data Center operations. Candidates should possess a strong background in high-performance computing and programming skills, particularly in Python, to effectively deploy and maintain production-grade machine learning systems.

Qualifications

• Strong background in high-performance computing.
• Experience managing large hardware clusters.
• Proficient in at least one programming language (e.g., Python).

Responsibilities

• Manage private large high-end GPU clusters.
• Handle full lifecycle of physical systems including deployment, operations, triage, and troubleshooting.
• Automate configuration of on-premises Linux-based systems using infrastructure-as-code practices.

Skills

Problem-solving

High-performance computing

Programming (Python)

Data Center operations

GPU optimization

Job description

1 month ago Be among the first 25 applicants

This range is provided by Boson AI. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

CA$150,000.00/yr - CA$250,000.00/yr

Boson AI is a startup building large language tools for everyone to use. Our founders (Alex Smola, Mu Li), and a team of Deep Learning, Optimization, NLP, AutoML, and Statistics scientists and engineers are working on high-quality generative AI models for language, audio, and entertainment.

About The Role

We are looking for a Senior High Performance Computing Engineer to help operate GPUs, network, and filesystem in our datacenter deployment in Toronto. The ideal candidate should have strong problem-solving skills and an ability to learn new tools. Experience with Slurm, MAAS, Ceph, Infiniband, NVIDIA DeepOps, Ethernet networking, and related tools is a big plus. You should be comfortable performing hardware configuration.

You will have the opportunity to work with NVIDIA H100 and A100 GPUs, over 20PB of storage, Terabit networking, and hundreds of computers. You will be responsible for deploying and operating a broad range of infrastructure technologies and hardware systems.

A day in the life:

• Manage private large high-end GPU clusters
• Handle full lifecycle of physical systems including deployment, operations, triage, and troubleshooting
• Configure and maintain network switches (Tomahawk Ethernet, Mellanox Infiniband)
• Configure and maintain MAAS, Ceph, Slurm, and Kubernetes
• Automate configuration of on-premises Linux-based systems using infrastructure-as-code practices
• Configure and maintain network, e.g., Layer 3 networking
• Learn about new tools and deploy them

You might be a great fit if you have:

• Strong background in high-performance computing
• Experience with on-premises Data Center operations and technologies
• Experience managing large hardware clusters
• Proficiency in at least one programming language (e.g., Python) and ability to write clean, maintainable code
• Experience designing, deploying, and maintaining production-grade machine learning systems at scale
• Familiarity with GPU utilization for machine learning workloads and optimization techniques
• Experience managing firmware and system updates for hardware, e.g., SuperMicro

The ability to solve problems and learn new techniques is key.

Seniority level

Not Applicable

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

Hospitality, Food and Beverage Services, and Retail

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