AI Research Scientist — Agentic AI and Foundation Models

Advanced Micro Devices, Inc • Santa Clara, CA

23h

About The Position

AMD is seeking an AI Research Scientist to advance language models and intelligent agents for complex technical and research tasks. The role explores how models acquire domain knowledge, reason, use tools, and learn through interaction with real development environments.

The work spans model training, agent design, and rigorous evaluation, with applications in software development, hardware design and verification, performance optimization, and automated technical discovery. Research may include pre-training, domain-adaptive continued pre-training, post-training, reinforcement learning, and inference-time reasoning and search. The scientist will own projects from initial research questions through working systems and demonstrated impact, developing models and agents that solve increasingly complex technical problems, generalize across projects and domains, and measurably improve software and hardware development quality and productivity.

The ideal candidate combines research depth with strong engineering skills, can turn ambiguous problems into experiments, and can identify whether model limitations stem from knowledge, reasoning, context, or tools. The role values original research as well as measurable results in practical settings. A Master’s or PhD in Computer Science, Machine Learning, Electrical Engineering, or a related field is preferred; candidates with equivalent research experience and demonstrated contributions are also encouraged to apply.

Requirements

• Strong research depth and engineering skills.
• Ability to turn ambiguous problems into experiments that improve model and agent capabilities.
• Ability to identify whether limitations stem from model knowledge, reasoning, context, or tools, and develop approaches to address them.
• Strong Python and deep learning framework skills, with experience running reproducible experiments.
• Master’s or PhD in Computer Science, Machine Learning, Electrical Engineering, or a related field preferred; equivalent research experience and demonstrated contributions are also encouraged.

Nice To Haves

• Strong publication record in language models, AI agents, reinforcement learning, code intelligence, automated reasoning, or related areas, including venues such as NeurIPS, ICML, ICLR, ACL, and EMNLP.
• Hands-on experience with LLM pre-training, continued pre-training, or post-training, including supervised fine-tuning and reinforcement learning.
• Experience building agents that interact with tools and executable environments.
• Experience developing training datasets, generating synthetic data, or learning from agent trajectories and verifiable feedback.
• Familiarity with distributed training, large-scale evaluation, or efficient inference.
• Experience applying AI to software development, hardware design, scientific computing, or optimization.
• Familiarity with RTL, simulation, formal verification, compilers, or GPU kernels.

Responsibilities

• Research methods for reasoning, planning, tool use, memory, and reliable execution of multistep tasks.
• Develop pre-training and post-training approaches to strengthen models’ technical knowledge, coding abilities, and problem-solving capabilities.
• Build learning pipelines using curated corpora, demonstrations, synthetic data, agent trajectories, and execution feedback.
• Apply reinforcement learning and other adaptation methods to improve agent performance in executable environments.
• Investigate inference-time reasoning and search to improve solution quality and computational efficiency.
• Develop agents for software and hardware workflows, including code generation, RTL optimization, debugging, verification, and performance analysis.
• Create benchmarks that measure correctness, generalization, and sustained performance across unfamiliar projects.
• Collaborate with software and hardware teams to translate research into useful capabilities.
• Publish research and share findings through technical reports, reusable systems, and working demonstrations.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior