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AMD
Santa Clara, California
Source: AMD careers · View original posting
From AMD's posting. “We” and “our” refer to the employer.
We are hiring AI Engineers to build recursive self-improvement systems for compute. This role sits at the intersection of AI systems, performance engineering, hardware-aware optimization, and agentic software development. You will help build systems where AI proposes improvements, verifies correctness, measures impact, learns from failures, and improves the next generation of compute workloads and platforms.
The work requires turning complex engineering tasks into repeatable optimization loops with clear inputs, candidate generation, automated validation, measurable scoring, and reliable iteration. You will work on problems where feedback may be expensive, correctness is non-negotiable, and small improvements can have large impact at scale.
You are a hands-on engineer who can move between modern AI methods, systems performance, and hardware-aware workflows. You are comfortable with fast-moving AI research, but you care most about measurable outcomes: correctness, speed, efficiency, quality, reproducibility, and engineering leverage. You can collaborate with research scientists, hardware engineers, software engineers, and external technical partners while keeping an end-to-end loop working.
We are hiring AI Engineers to build recursive self-improvement systems for compute. This role sits at the intersection of AI systems, performance engineering, hardware-aware optimization, and agentic software development. You will help build systems where AI proposes improvements, verifies correctness, measures impact, learns from failures, and improves the next generation of compute workloads and platforms.
The work requires turning complex engineering tasks into repeatable optimization loops with clear inputs, candidate generation, automated validation, measurable scoring, and reliable iteration. You will work on problems where feedback may be expensive, correctness is non-negotiable, and small improvements can have large impact at scale.
You are a hands-on engineer who can move between modern AI methods, systems performance, and hardware-aware workflows. You are comfortable with fast-moving AI research, but you care most about measurable outcomes: correctness, speed, efficiency, quality, reproducibility, and engineering leverage. You can collaborate with research scientists, hardware engineers, software engineers, and external technical partners while keeping an end-to-end loop working.
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