The role involves hiring AI Engineers to develop recursive self-improvement systems for compute, focusing on AI systems, performance engineering, and hardware-aware optimization. Engineers will create systems that enable AI to propose improvements, verify correctness, and learn from failures. The position emphasizes measurable outcomes such as correctness, speed, and efficiency while collaborating with various technical teams. This role is integral to advancing the next generation of compute workloads and platforms.

• Strong software engineering experience in Python and at least one systems language such as C++, C, HIP, or CUDA.
• Experience building AI, ML, agentic, optimization, or automation systems evaluated with objective metrics.
• Ability to design reliable experiment loops, benchmark harnesses, and validation workflows.
• Strong technical judgment in debugging, profiling, and performance-oriented iteration.
• Clear communication skills to work across AI research, hardware, software, and partner-facing teams.

• Build agentic and learning-driven optimization loops for compute workloads and hardware engineering workflows.
• Develop systems that generate, compile, test, benchmark, profile, and iterate on candidate improvements with minimal human intervention.
• Convert high-value engineering workflows into verifiable tasks with clear graders, harnesses, metrics, and failure feedback.
• Collaborate with AI researchers on reward design, shaping, and long-horizon optimization.
• Design feedback systems that accumulate useful data from successful and failed attempts.
• Improve iteration speed through staged validation, caching, and parallel execution.
• Build reusable tools and patterns that generalize across multiple compute and hardware optimization domains.
• Mentor other engineers and help set technical direction for self-improving AI systems.

• AMD provides a competitive 'Total Rewards' package that focuses on financial growth, health, and work-life balance.