WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ THE ROLE: We are seeking an AI Systems Engineer to join our AMD IT compute platforms engineering team. The AI Systems Engineer is responsible for the design, development, and administration of High-Performance Computing (HPC) infrastructure, GPU clusters, and AI workload schedulers. THE PERSON: You have a passion for learning. You are passionate about the field of large-scale distributed computing in AI and HPC workloads. You take responsibility for end-to-end outcomes of your efforts. You want to build scalable and highly performant HPC/AI/Data services with AMD hardware, software, people and processes. You have a curiosity to learn and improve scalable HPC systems. You have significant experience in working across a globally distributed organization. KEY RESPONSIBILITIES: Support and develop existing AI applications both front and backend Develop, implement, and maintain GPU-based clusters, ensuring optimal performance Administer ML/AI platforms – Distributed ML services, LLMs, Vector-DB and AI inferencing, by managing deployments, resource allocation, monitoring, and security. 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 that they adhere to industry best practices and meet company standards. Use AI/ML to continuously improve internal processes and tools that are used in end-to-end delivery of your services in this team PREFERRED EXPERIENCE: Experience in HPC infrastructure engineering for AI/HPC domain Managing GPU clusters optimizing GPU-based services/tools/software Proficiency in RoCEv2, K8s, KVM, Ubuntu, Python, Shell, Go, Rust, GPU drivers, and Cluster interconnect with 200G/400G networking. Experience in creating web services with HPC backend (like AI) Experience in developing python based AI apps and UI Demonstrated experience with AI workload schedulers and allocation optimization. Strong organizational, problem-solving, and troubleshooting skills, with the ability to manage multiple projects simultaneously. Excellent verbal and written communication skills, with the ability to collaborate effectively with team members and stakeholders at all levels of the organization. Location: San Jose #LI-MF2 #LI-HYBRID At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here. 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.