Senior HPC AI Engineer

NVIDIA is looking for an experienced HPC Engineer to join the E2E software verification HPC/AI Infrastructure team. We are focused on building supercomputers and HPC clusters based on groundbreaking technologies. We are looking for an outstanding architect for a senior HPC position, to be a key player in the most exciting computing hardware and software, contributing 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, collaborating with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialists to architect, develop, and bring up large scale performance platforms.

What you will be doing:

1. Design, implement and maintain large scale HPC/AI clusters with monitoring, logging and alerting.
2. Manage Linux job/workload schedules and orchestration tools.
3. Develop and maintain continuous integration and delivery pipelines.
4. 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.
5. Deploy monitoring solutions for the servers, network, and storage.
6. Perform troubleshooting from bare metal, operating system, software stack, and application level.
7. Being a technical resource, develop, redefine, and document standard methodologies to share with internal teams.
8. Support Research & Development activities and engage in POCs/POVs for future improvements.

What we need to see:

1. A degree in Computer Science, Engineering, or a related field and 5+ years of experience.
2. Knowledge of HPC and AI solution technologies from CPUs and GPUs to high speed interconnects and supporting software.
3. Experience with job scheduling workloads and orchestration tools such as Slurm, K8s.
4. Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalld, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc.
5. Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies.
6. Python programming and bash scripting experience.
7. Comfortable with automation and configuration management tools such as Jenkins, Ansible, Puppet/Chef.
8. Deep knowledge of Networking Protocols like InfiniBand, Ethernet.
9. Deep understanding and experience with virtual systems (for example VMware, Hyper-V, KVM, or Citrix).
10. Familiarity with cloud computing platforms (e.g. AWS, Azure, Google Cloud).

Ways to stand out from the crowd:

1. Knowledge of CPU and/or GPU architecture.
2. Knowledge of Kubernetes, container-related microservice technologies.
3. Experience with GPU-focused hardware/software (DGX, Cuda).
4. Background with RDMA (InfiniBand or RoCE) fabrics.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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