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High-Performance Computing Architect
hace 1 mes
We are seeking an experienced HPC Engineer to join our E2E software verification HPC/AI Infrastructure team. As a key player in building supercomputers and HPC clusters, you will contribute to the latest breakthroughs in artificial intelligence and GPU computing.
You will provide insights on at-scale system design and tuning mechanisms for large-scale compute runs. You will work with the latest accelerated computing and deep learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions.
Key Responsibilities:
- Design, implement and maintain large scale HPC/AI clusters with monitoring, logging and alerting.
- Manage Linux job/workload schedules and orchestration tools.
- Develop and maintain continuous integration and delivery pipelines.
- Develop tooling to automate deployment and management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources.
- Deploy monitoring solutions for the servers, network and storage.
- Perform troubleshooting from bare metal, operating system, software stack, and application level.
- Being a technical resource, develop, re-define and document standard methodologies to share with internal teams.
- Support Research & Development activities and engage in POCs/POVs for future improvements.
Requirements:
- A degree in Computer Science, Engineering, or a related field and 5+ years of experience.
- Knowledge of HPC and AI solution technologies from CPUs and GPUs to high speed interconnects and supporting software.
- Experience with job scheduling workloads and orchestration tools such as Slurm, K8s.
- Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking and internals, ACLs and OS level security protection, and common protocols e.g. TCP, DHCP, DNS, etc.
- Experience with multiple storage solutions such as Lustre, GPFS, zfs, and xfs. Familiarity with newer and emerging storage technologies.
- Python programming and bash scripting experience.
- Comfortable with automation and configuration management tools such as Jenkins, Ansible, Puppet/Chef.
- Deep knowledge of Networking Protocols like InfiniBand and Ethernet.
- Deep understanding and experience with virtual systems (for example VMware, Hyper-V, KVM, or Citrix). Familiarity with cloud computing platforms (e.g. AWS, Azure, Google Cloud).
Preferred Qualifications:
- Knowledge of CPU and/or GPU architecture.
- Knowledge of Kubernetes, container related microservice technologies.
- Experience with GPU-focused hardware/software (DGX, Cuda).
