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AMD

Designs chips for computers and AI systems

HPC Systems Engineer - AI Workloads

Platform EngineeringPosted on Nov 13
Full-timeSan Jose, CA, USANo salary listedIn-person

About the Job

Requirements

  • Significant experience working across a globally distributed organization.
  • Experience developing Python-based AI applications and user interfaces is preferred.
  • Experience in HPC infrastructure engineering for AI/HPC domains is preferred.
  • Experience managing SLURM and Kubernetes is preferred.
  • Experience managing GPU clusters and optimizing GPU-based services, tools, and software is preferred.
  • Experience creating web services with an HPC backend is preferred.
  • Proficiency in RoCEv2, Kubernetes, KVM, Ubuntu, Python, Shell, GPU drivers, and cluster interconnects with 400G networking is preferred.
  • Demonstrated experience with AI workload schedulers and allocation optimization is preferred.
  • Experience with automation and monitoring tools, including Ansible or SaltStack, Terraform, Prometheus, and Grafana, is preferred.
  • Strong organizational, problem-solving, and troubleshooting skills, with the ability to manage multiple projects simultaneously, are preferred.
  • Bachelor's or master's degree in computer science or computer engineering is preferred.
  • Excellent verbal and written communication skills and the ability to collaborate effectively with team members and stakeholders at all levels are preferred.

Responsibilities

  • Develop, implement, and maintain GPU-based clusters, ensuring optimal performance.
  • Administer machine learning and AI platforms, including distributed machine learning services, large language models, and AI inferencing, by managing deployments, resource allocation, monitoring, and security.
  • Automate system provisioning and cluster management end to end.
  • Collaborate with cross-functional teams to address AI infrastructure requirements, support AI-related projects, and provide technical expertise.
  • Monitor and evaluate the performance of AI systems and clusters, ensuring they adhere to industry best practices and meet company standards.
  • Use AI and machine learning to continuously improve internal processes and tools used in the end-to-end delivery of team services.

Desired Qualifications

  • Experience developing Python-based AI applications and user interfaces.
  • Experience in HPC infrastructure engineering for AI/HPC domains.
  • Experience managing SLURM and Kubernetes.
  • Experience managing GPU clusters and optimizing GPU-based services, tools, and software.
  • Experience creating web services with an HPC backend.
  • Proficiency in RoCEv2, Kubernetes, KVM, Ubuntu, Python, Shell, GPU drivers, and cluster interconnects with 400G networking.
  • Demonstrated experience with AI workload schedulers and allocation optimization.
  • Experience with automation and monitoring tools, including Ansible or SaltStack, Terraform, Prometheus, and Grafana.
  • Strong organizational, problem-solving, and troubleshooting skills, with the ability to manage multiple projects simultaneously.
  • Excellent verbal and written communication skills and the ability to collaborate effectively with team members and stakeholders at all levels of the organization.
  • Bachelor's or master's degree in computer science or computer engineering.

About the Company

AMD

Designs chips for computers and AI systems

AMD designs processors, graphics chips and AI accelerators for computer makers, cloud operators and businesses that build electronic devices. Its Ryzen processors power personal computers, while EPYC processors handle work in data centers and Radeon chips render graphics. Instinct accelerators run AI models, paired with software that developers use to train models and put them into production. AMD sells chips and related computing systems through equipment makers, distributors and retail channels, and contracts with outside foundries to fabricate its semiconductor designs. It was founded in 1969 and has its headquarters in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1969

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