Original listing text, shown exactly as published by the company.
What You’ll Do
- Remotely deploy and configure large-scale HPC clusters for AI workloads (up to many thousands of nodes)
- Remotely install and configure operating systems, firmware, software, and networking on HPC clusters both manually and using automation tools
- Troubleshoot and resolve HPC cluster issues working closely with physical deployment teams on-site
- Provide clear and detailed requirements back to other engineering teams on gaps and improvement areas, specifically in the areas of simplification, stability, and operational efficiency
- Contribute to the creation of and maintenance of Standard Operating Procedures
- Provide regular and well-communicated updates to project leads throughout each deployment
- Mentor and assist less experienced team members
- Stay up-to-date on the latest HPC/AI technologies and best practices
You
- Are a deeply experienced HPC engineer comfortable with logical provisioning of a cluster
- Have a strong understanding of HPC/AI architecture, operating systems, firmware, software, and networking
- 5+ years of experience in deploying and configuring HPC clusters for AI workloads
- Have an innate attention to detail
- Are in expert in configuring and troubleshooting:
- SFP+ fiber, Infiniband (IB), and 100 GbE network fabrics
- Ethernet, switching, power infrastructure, GPU direct, RDMA, NCCL, Horovod environments
- Linux based compute nodes, firmware updates, driver installation
- SLURM, Kubernetes, or other job scheduling systems
- Work well under deadlines and structured project plans also knowing when and how to ask for changes to project timelines
- Have excellent problem solving and troubleshooting skills
- Have flexibility to travel to our North American data centers as on-site needs arise or as part of training exercises
- Are able to work independently and as part of a team
- Are comfortable mentoring and supporting junior HPC engineers on cluster deployments
Nice to Have
- Experience with machine learning and deep learning frameworks (PyTorch, Tensorflow) and benchmarking tools (DeepSpeed, MLPerf)
- Experience with containerization technologies ( Docker, Kubernetes)
- Experience working with the technologies that underpin our cloud business ( GPU acceleration, virtualization, and cloud computing)
- Keen situational awareness in customer situations, employing diplomacy and tact
- Bachelors degree in EE, CS, Physics, Mathematics, or equivalent work experience
Salary Range Information
The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
