Engineering Manager, HPC Kubernetes Platform
Engineering Manager, HPC Kubernetes Platform
Location: Dallas, TX
Overview
This organization is backed by dedicated leadership and investment, with a clear mission as it operates at the bleeding edge of technology. Its goal is to scale and enhance high-performance computing (HPC) and cloud infrastructure that supports clients' research, production, and delivery, enabling breakthroughs that shape the industries of tomorrow. Its engineers build critical infrastructure to eliminate friction in scientific research, simulations, analysis, and decision-making, accelerating discovery and driving faster innovation.
We are seeking an experienced Engineering Manager, HPC Kubernetes Platform to lead the team responsible for designing and scaling a bare-metal Kubernetes environmentâthe orchestration layer powering GPU- and CPU-intensive machine-learning and HPC workloads across global datacenters.
This is a hands-on leadership role focused on platform performance, reliability, and automation. You will define the technical roadmap, guide system architecture and optimization, and ensure the Kubernetes platform delivers top-tier reliability and throughput for distributed ML and HPC environments. The ideal candidate is a strong technical leader who thrives at the intersection of infrastructure engineering, AI systems, and high-performance computing.
Key Responsibilities
- Lead and mentor engineers designing and scaling a bare-metal Kubernetes platform for HPC and ML workloads.
- Architect and optimize GPU/CPU scheduling, resource management, and performance across multi-tenant compute clusters.
- Drive automation and observability using Infrastructure-as-Code, CI/CD, and SRE best practices.
- Collaborate with Research, Storage, and Network teams to integrate distributed filesystems, high-speed interconnects (InfiniBand, RoCE), and custom runtimes.
- Partner with hardware and software vendors to improve tooling, influence product roadmaps, and streamline deployment.
- Oversee platform reliability, capacity forecasting, and performance KPIs across thousands of nodes.
Required Experience
- 7+ years in infrastructure, platform, or SRE engineering, including 2+ in technical leadership.
- Proven experience operating Kubernetes environments tailored for HPC or ML training workloadsâGPU scheduling, resource isolation, and workload optimization.
- Deep knowledge of Linux systems, networking, and performance engineering on bare-metal hardware.
- Experience managing large-scale, multi-tenant clusters and integrating distributed storage or high-speed networking.
- Strong automation experience (Terraform, Ansible, or similar) and familiarity with observability tools (Prometheus, Grafana, Loki).
- Excellent communication and stakeholder management skills; ability to translate complex technical direction into clear, actionable plans.
- Bachelor's degree or equivalent experience.
Preferred Experience
- Familiarity with HPC schedulers (Slurm, Flux) and container runtimes (containerd, CRI-O).
- Contributions to open-source Kubernetes or ML infrastructure projects.
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