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# AI Research Scientist, Reinforcement Learning (LLM) and Post-Training

- **Company:** Advanced Micro Devices, Inc.
- **Location:** Santa Clara, CA, United States
- **Salary:** $204,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Machine Learning, Reinforcement Learning, Data Logging, Graphics Processing Unit (GPU), Large Language Models, Information Technology
- **Published:** July 2, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/87630270/1

## About the Role

* Strong publication record in reinforcement learning or closely related machine learning areas.
 * Hands-on experience training RL or preference-optimized models at non-trivial scale (GPUs, distributed jobs)
 * Experience with LLM post-training, RLHF/RLAIF, or policy optimization for language or code agents
 * Familiarity with compilers, kernels, EDA-style workflows, or large-scale codebases is a plus

ACADEMIC CREDENTIALS:

 * PhD in Computer Science, Machine Learning, or related field strongly preferred.

## Description

We are hiring a Lead AI Research Scientist, Reinforcement Learning (LLM) and Post-Training, specializing in reinforcement learning to advance post-training and interactive learning for large generative models applied to demanding engineering and hardware-adjacent tasks (code, optimization, tool use, and long-horizon decision making). You will invent and analyze RL algorithms-policy optimization, preference-based methods, exploration, credit assignment, and reward modeling-run rigorous empirical studies, and partner with infra and product teams to land methods that improve measurable task success without sacrificing stability or safety., * Research and develop RL methods for post-training LLMs and code models on structured engineering tasks with verifiable or preference-based feedback

 * Design reward models, curricula, and off-policy or on-policy training recipes suited to sparse, noisy, or expensive labels from experts and simulators
 * Characterize failure modes (reward hacking, degenerate policies, instability) and propose mitigations grounded in experiments
 * Collaborate with RL infra engineers to scale training; define interfaces for rollout generation, logging, and reproducibility
 * Publish at top venues (e.g. NeurIPS, ICML, ICLR) and contribute internal technical leadership on the RL roadmap, AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.


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