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 |
|---|---|---|
| Staff AI Research Engineer AMD is seeking a Staff AI Research Engineer to join their Llama team. The role involves researching, prototyping, and implementing cutting-edge generative AI techniques, including post-training reasoning and RL methods. A key responsibility is translating these advanced AI concepts into clear educational content for a broad developer audience, leveraging AMD's high-performance chips. The position also requires staying current with AI research and contributing to internal knowledge sharing, with potential development in GPU kernel writing and DSLs. | Post-train | 8 |
| Technical Marketing Engineer – AI Training Workloads & Performance Technical Marketing Engineer focused on AI training workloads and performance optimization for AMD GPUs. The role involves creating technical content, analyzing performance bottlenecks, and enabling customers to achieve optimal results across various stages of the AI model lifecycle, from pre-training to fine-tuning and reinforcement learning. |
| Post-trainPretrain |
| 8 |
