AI/HPC Infrastructure Software Engineer

AI/HPC Infrastructure Software Engineer

  

This role has been designated as ‘Remote/Teleworker’, which means you will primarily work from home.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know diverse backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

   

Artificial Intelligence (Generative AI and all of Machine and Deep Learning) and High-Performance Computing are the fastest growing workloads in the industry today.   These workloads are pushing the leading edge of networking technology forward at a rapid pace.  Come join the Slingshot Ethernet Fabric team, part of HPE's HPC and AI organization, and make an impact on the high-performance fabric business.

We are looking for an Infrastructure Software Engineer to help expand HPE's High Performance Ethernet Fabric product growth through the development of the network infrastructure capabilities necessary for AI/ML and HPC workloads and applications.  This includes directly working with the open-source communities to optimize and support the latest system solutions including Kubernetes workload and orchestration for Slingshot based clusters, resource management solutions (e.g. Slurm or PBS Pro), and other system capabilities necessary to deploy, manage, and maintain a scale AI cluster, system, and workload.   

Join the HPE AI Fabric team and be a part of the growth and evolution of Artificial Intelligence (AI), high speed networking fabrics, and the fastest growing and most significant technology revolution since the Internet. 

Responsibilities include, but are not limited to:

• Engage and work with the GPU/CPU vendors, customers, AI ISV and open-source SW communities to validate, tune, and enable high performance AI applications on the Slingshot Ethernet fabric.
• Work on partner engagements for the leading communication libraries, middleware and frameworks used in AI development today (NCCL, RCCL, UCX, OneCCL. Pytorch, etc.).
• Design, implement and maintain system software that enables communication between GPUS, CPUs, and storage in scale out AI and HPC systems.  Work with all the leading architectures and vendors in the AI and Data Center markets – Nvidia, AMD, Intel.
• Work with the OEM, ODM, and VAR channels vendors on bring Slingshot to a broader set of customers. Validate and tune applications driving those engagements. 
• Develop and own HPE product usage support, upstreaming and community engagements, and internal testing and infrastructure.
• Work with cross-disciplinary teams to understand business requirements and align software direction to meet those needs.

Qualifications should Include:

• Bachelor’s/master's degree in computer science, engineering, or related field
• 5+ years of relevant experience with a background in networking and communications software development and/or architecture in the Data Center, university, government lab, or AI-centric environments.

• Experience in scripting programming using languages such as Python, Go, and bash scripting.
• Experience with HPC(High-Performance Computing), concepts, and the applications that drive this field.
• Experience with large cluster deployment and management
• Familiarity with low-latency/high-bandwidth, interconnected infrastructure (including InfiniBand, Ethernet, RDMA/RoCE, and others).
• Knowledge of HPC storage (FC, SAS) principles, file systems (NFS, Lustre, ZFS, etc.), and compute node storage, Network Attached Storage.
• Experience in setting up and managing monitoring solutions (Elasticsearch, Logstash, Prometheus, Grafana, Kibana, etc.)
• In-depth understating of container technologies like Docker, Containerd, Singularity, Podman
• Good Understanding of Kubernetes environments (deployments, storage, services, jobs, ingress, egress, etc)
• Experience with Kubernetes extensions (device-plugins, CRD, CNIs, and C