HPC - AI/ML Platform Engineer
About The Position
The selected candidate will join the team responsible for engineering and operating large-scale GPU and compute platforms that power AI/ML and high performance computing workloads across multiple datacenters. The team manages Kubernetes-based GPU environments, cluster infrastructure, and the supporting systems that enable internal engineering teams to train models, run simulations, and develop advanced software at scale. This role focuses on building reliable, scalable GPU platforms and helping internal users successfully run AI/ML and high-performance workloads on Kubernetes and related compute infrastructure.
Requirements
- 5+ years of Linux systems engineering or infrastructure experience
- 2+ years working with container platforms such as Kubernetes or OpenShift
- Familiarity with Kubernetes GPU scheduling and related tooling
- Familiarity with CI/CD pipelines and platform engineering practices
- Experience operating compute infrastructure for high-performance workloads or large distributed systems
- Strong scripting or programming skills (Python, Bash, or similar)
- Experience building infrastructure automation and operational tooling
- Strong troubleshooting and problem-solving skills across complex infrastructure systems
- Ability to communicate clearly with both platform engineers and application teams
- Demonstrated ability to manage multiple technical initiatives simultaneously
Nice To Haves
- Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience
- Experience with observability platforms such as Prometheus, Grafana, or similar
- Experience with infrastructure automation tools (Ansible, Terraform, etc.)
- Experience with high-speed networking technologies such as InfiniBand or RDMA
Responsibilities
- Design, implement, and support GPU/Kubernetes clusters and supporting infrastructure
- Supporting AI/ML training, simulation, and HPC workload customers
- Develop automation and tooling for cluster provisioning, configuration management, and platform operations
- Collaborate with application and research teams to optimize workloads running on GPU infrastructure
- Implement monitoring, observability, and performance tuning across GPU and compute platforms
- Troubleshoot infrastructure issues across compute, networking, and container platforms (occasional on-call support)
- Contribute to platform reliability, scalability, and operational best practices
- Produce clear technical documentation and operational runbooks
Benefits
- Immediate medical, dental, and prescription drug coverage
- Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and more
- Vehicle discount program for employees and family members, and management leases
- Tuition assistance
- Established and active employee resource groups
- Paid time off for individual and team community service
- A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
- Paid time off and the option to purchase additional vacation time.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
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