Senior GPU Kubernetes Engineer

WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. The Role AMD’s Software and Solutions Team is seeking a Senior GPU Kubernetes Engineer to lead GPU operator development, advanced scheduling strategies, and deployment automation for the AMD Enterprise AI Suite. This role requires strong Kubernetes engineering expertise, deep understanding of GPU resource management, and hands-on experience optimizing AI workloads in cloud and on-prem environments.

The Senior GPU Kubernetes Engineer will help define next-generation GPU orchestration, improve workload predictability and utilization, and design scalable automation for distributed inference, fine-tuning, and LLM-based services. The work spans operator development, cluster optimization, autoscaling logic, Helm-based deployment patterns, and integration with AMD’s GPU software stack.

The Person A highly motivated and passionate professional with deep expertise in Kubernetes, GPU acceleration, and cloud-native deployment systems, with a proven track record in problem-solving, collaboration, and technical execution

Key Responsibilities

• Lead GPU Operator development; implement topology-aware scheduling policies; optimize NUMA placement, PCIe locality, and memory bandwidth; and ensure robust integration with AMD’s ROCm drivers and runtimes.
• Design autoscaling logic for GPU-heavy inference and fine-tuning workloads, build monitoring and telemetry instrumentation, strengthen workload reliability, and develop scalable Helm charts and automation workflows.
• Collaborate closely with ROCm, platform, performance, and model teams to ensure end-to-end integration quality; troubleshoot across GPU runtimes, Kubernetes layers, and AI frameworks; influence AMD’s Kubernetes roadmap; and support deployment models across customer, partner, and ecosystem environments.

Preferred Experience

• Strong hands-on experience with Kubernetes GPU workloads, Operator/CRD development, scheduling plugins, and resource managers. Proficiency with Helm, Kustomize, Prometheus, Grafana, FluentD/FluentBit, and ArgoCD is valuable.
• Deep understanding of NUMA, GPU topology, affinity/anti-affinity rules, and multi-GPU inference strategies is essential.
• Familiarity with distributed inference frameworks such as vLLM, Triton, KServe, or Ray, along with experience deploying LLM workloads, is highly desirable.
• Knowledge of ROCm, AMD MI300/MI325 platforms, OpenShift, KubeVirt, or enterprise Kubernetes systems provides a strong advantage.

Academic Credentials

• BS, MS, or PhD in Computer Science or a related equivalent

This role is not eligible for visa sponsorship. Benefits offered are described: AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.