Senior ML/AI DevOps Engineer

Advanced Micro Devices, Inc•Santa Clara, CA

About The Position

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 ML/AI DevOps Engineer to drive automated infrastructure deployment, CI/CD design, and validation workflows for AMD’s AI software and datacenter platforms. This role requires deep technical expertise in infrastructure automation, cloud-native systems, and DevOps engineering, along with strong cross-functional collaboration skills. The position spans development, deployment, performance validation, and monitoring, ensuring highly reliable and secure infrastructure to support AMD’s rapidly evolving AI initiatives. THE PERSON: A highly motivated and passionate professional with deep expertise in DevOps, automation engineering, and infrastructure orchestration, combined with a strong track record of collaboration, technical execution, and systems integration

Requirements

BS, MS, or PhD in Computer Science or a related equivalent + 6 Years of applicable experience

Nice To Haves

Extensive expertise in Python automation, CI/CD frameworks (Jenkins, Terraform, Ansible), and Kubernetes/Helm-based microservice deployment.
Strong experience with Docker container development, GitHub Actions, Linux system administration, and networking fundamentals (PXE, IPMI, switching/routing) is highly valuable.
A solid understanding of observability tools such as Prometheus, Grafana, or ELK/Kibana, along with best practices in secure development and scalable automation, is necessary to optimize workflow performance and maintain reliability across AMD’s AI DevOps infrastructure.

Responsibilities

Create resilient automation pipelines, orchestrate Kubernetes-based environments, and ensure seamless integration of diverse software components.
Design CI/CD pipelines, automate bare-metal-to-Kubernetes bring-up, deploy microservices with Helm, and integrate security and static code analysis tools.
Build monitoring systems and automated alerts, diagnose and resolve complex build failures, and collaborate with teams across the organization to ensure validation readiness for AI solutions.
Play a critical role in advancing AMD’s infrastructure, scaling enterprise deployment workflows, refining automation architectures, and enabling rapid iteration across the Software and Solutions organization.