Machine Learning Systems Research Engineer, Multiple Teams

AMD is hiring a Machine Learning Systems Research Engineer to build reinforcement learning, inference, and evaluation infrastructure for AI-for-engineering systems. The role focuses on creating scalable ML systems that support agentic workflows, including job orchestration, reward design, and tool-use pipelines for LLM agents. You will collaborate with AI researchers and engineers to improve model performance through reproducible experimentation, robust infrastructure, and advanced reward design.

• Build RL and inference systems for agentic engineering workflows, including job orchestration, sampling, scoring, caching, experiment tracking, and reproducible evaluation.
• Develop infrastructure for long-horizon and high-latency reward tasks where validation can take minutes to hours.
• Design staged rewards, proxy graders, sliced evaluation paths, retry strategies, and uncertainty-aware evaluation methods.
• Support optimization workflows with systems for candidate generation, benchmark execution, correctness checking, profiler feedback, reward modeling, and model-level improvement.
• Partner with AI research scientists on reward hacking research, reward shaping, metareasoning, and post-training methods for engineering tasks.
• Build scalable inference and tool-use pipelines for LLM agents that interact with compilers, profilers, simulators, formal tools, benchmark harnesses, and internal knowledge sources.