AMD currently has 35 active AI-related job listings. The majority of these roles, 66%, are focused on serving infrastructure. Engineering is the dominant function, with 32 positions. Frequent technical tags include model_serving, inference_infra, and evals, suggesting a focus on the deployment and evaluation of AI models. In the last 30 days, AMD posted 37 new AI roles.
AMD currently has 59 active AI-related roles in our index. The most common open titles are: Data Center Engineer (2), Lead Packaging Automation Engineer (2), Software Development Engineer (2), AI Framework Engineer, AI Software Development Eng.. Most positions are in Engineering and Research.
AMD's active AI hiring is concentrated in: serving infrastructure (54%), agents (19%), application (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
AMD is hiring AI talent in: United States (29 roles), India (8 roles), Poland (6 roles), China (5 roles).
Job postings at AMD most frequently reference: model serving, inference infra, fine tuning, agent orchestration, evals.
In the past 30 days, AMD has posted 68 new AI-related roles. That is a +209% change versus the prior 30 days (22 → 68).
| Title | Stage | AI score |
|---|---|---|
| Director of Software Validation Engineering – ROCm Director of Test Engineering for ROCm software stack, focusing on AI training, inference, and HPC workloads. The role involves leading and transforming the quality function by scaling the team's impact through AI and agentic tooling, building an autonomous quality organization. Responsibilities include defining test strategy, building continuous testing infrastructure, and driving adoption of AI-assisted testing workflows. | ShipServe | 8 |
| Principal Staff Software Developer – AI/ML Performance Validation & Systems Testing Principal Staff Software Developer focused on AI/ML performance validation and systems testing for AMD's ROCm software stack. The role involves owning the end-to-end validation architecture, defining release-qualification gates, leading system-level testing, and driving compute workload validation for LLM training/inference and other AI/HPC workloads. Requires deep experience in GPU compute software, deep-learning frameworks, and agentic AI engineering environments, with a focus on shipping software for hyperscalers and OEMs. |
| ShipServe |
| 7 |
