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 support and operate advanced GPU and network systems essential for their cutting-edge AI technologies. This full-time role in Toronto involves managing high-performance computing clusters and ensuring optimal operation of infrastructure technologies, making it an ideal position for those passionate about optimizing machine learning systems.

Qualifications

• Experience managing a large hardware cluster.
• Ability to configure and maintain network switches.
• Familiarity with GPU utilization for machine learning workloads.

Responsibilities

• Manage private large high-end GPU clusters.
• Responsible for full lifecycle of physical systems.
• Automate on-premises Linux-based systems at scale.

Skills

Problem Solving

Strong background in high performance computing

Proficiency in Python

Experience with Data Center operations

Tools

Slurm

MAAS

Ceph

NVIDIA DeepOps

Infiniband

Job description

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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 us operate the GPUs, network and filesystem in our datacenter deployment in Toronto. The ideal candidate needs to 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 are a big plus. You should be comfortable performing some amount of 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
• Responsible for full lifecycle of physical systems including deployments of new hardware, operations, triage and troubleshooting
• Configure and maintain network switches (Tomahawk Ethernet, Mellanox Infiniband)
• Configure and maintain MAAS, Ceph, Slurm and Kubernetes
• Configure and automate on-premises Linux-based systems at scale 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 with on-premises Data Center operations and technologies
• Experience in managing a large hardware cluster
• Proficiency in at least one programming language (e.g. Python) and ability to write clean, maintainable code
• Experience in designing, deploying, and maintaining production-grade machine learning systems at scale
• Familiarity with GPU utilization for machine learning workloads and optimization techniques
• Experience with managing firmware / systems updates for systems, e.g. on SuperMicro
  
  
  

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

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Research Services

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