ML Systems Engineer for RL & Inference Infrastructure

Advanced Micro Devices; Santa Clara (CA); Hybrid; USD 160,000 - 210,000; Full time

Benefits offered by this job

AMD benefits

Job summary

AMD in Santa Clara, CA is seeking an ML Systems Research Engineer to build reinforcement learning, inference, and evaluation infrastructure behind AI-for-engineering systems. You will enable many attempts, evaluate correctness, measure performance, and feed results back into model and agent improvements.

You will work across compute optimization, hardware automation, verification, and simulation, focusing on scalable systems that make research practical, repeatable, and useful for production

Qualifications

• Bachelor's degree in CS/CE/EE/ML or related field required.
• Master's degree preferred; PhD a plus in ML systems or related areas.
• Experience with ML systems, RL, distributed systems is valued.

Responsibilities

• 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.
• Standardize datasets, eval definitions, run logs, leaderboards, failure taxonomies, and data collection for future training.
• Analyze experimental results and turn system behavior into actionable guidance for model, agent, tool, and reward improvements.

Skills

Python programming

ML frameworks (PyTorch, JAX, TensorRT)

Distributed experimentation

System design & reliability

Experiment design & statistics

Collaboration skills

Education

Bachelor's degree in CS/CE/EE/ML

Master's degree preferred

PhD a plus

Tools

Kubernetes

Ray

Slurm

Workflow engines

Profiling tools

Job description

AMD in Santa Clara, CA is seeking an ML Systems Research Engineer to build reinforcement learning, inference, and evaluation infrastructure behind AI-for-engineering systems. You will enable many attempts, evaluate correctness, measure performance, and feed results back into model and agent improvements.

You will work across compute optimization, hardware automation, verification, and simulation, focusing on scalable systems that make research practical, repeatable, and useful for production