below marketmost similar roles pay hereabove market
This role pays more than
81%
of similar roles. Most pay
$175,000–$250,425
— the blue band above.
At the midpoint, this role pays about
$255k
versus about
$213k
for comparable roles.
Based on 240 similar postings.
Employer
About Amd
AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors
Amd currently has
496 open roles
on FindRole.
Listed pay typically runs
$172,000–$258,000
across 496 roles with salary data.
The Forward Deployed AI Research Scientist joins the team to bridge the gap between technical-business goals and AI engineering reality. This role involves identifying high-value AI opportunities in compute, systems, software, and hardware engineering workflows for internal and external stakeholders. You will translate customer needs into research questions, build prototypes, and evaluate modern AI methods including agentic workflows, tool use, code generation, debugging, optimization, retrieval, and learning from feedback. Key responsibilities include defining metrics, benchmarks, and acceptance criteria while creating technical narratives for senior stakeholders. Required skills include proficiency in Python and ML frameworks like PyTorch, JAX, or TensorFlow. You will apply generative AI, LLMs, and retrieval methods to solve problems involving correctness, performance, latency, reliability, and explainability within semiconductor and high-performance computing environments.
Identify high-value AI opportunities in compute, systems, software, and hardware engineering workflows with internal and external stakeholders.
Translate customer and partner needs into research questions, technical plans, evaluation criteria, and prototype paths.
Prototype and evaluate modern AI methods for engineering tasks like agentic workflows, code generation, and debugging.
Define metrics, benchmarks, and acceptance criteria for AI-assisted workflows in partnership with research and engineering teams.
Build technical narratives, demos, and decision materials to communicate tradeoffs and strategic value to senior stakeholders.
Convert recurring customer needs into reusable insights for product, research, platform, and engineering roadmaps.
Mentor teams on practical AI methods to improve the quality of experimentation, evaluation, and communication across the organization.
What we're looking for
Strong background in AI, machine learning, systems, or applied research with the ability to turn ideas into prototypes and measurable experiments.
Experience with modern generative AI methods, LLMs, agents, tool use, retrieval, post-training, evaluation, or applied ML systems.
Strong programming ability in Python and familiarity with ML frameworks such as PyTorch, JAX, TensorFlow, or similar.
Ability to communicate complex AI and systems topics clearly to both technical and executive audiences.
Experience in forward-deployed engineering, customer engineering, applied research, technical partnerships, solutions architecture, or strategic technical programs (preferred).
Experience with GPU systems, CPU performance, compilers, distributed training/inference, hardware/software co-design, or performance engineering (preferred).
Experience designing benchmarks, evals, experiment platforms, or metrics for AI systems (preferred).
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or related field, or equivalent practical experience.
Master's degree preferred; PhD is a plus, especially in AI, ML systems, computer systems, GPU computing, or hardware/software co-design (preferred).
Python
C++
Rust
C
TypeScript
CUDA
HIP
PyTorch
Hugging Face
JAX
TensorFlow
Ray
vLLM
LLM Post-training
Reinforcement Learning
RLHF
PPO
DPO
GRPO
Preference Optimization
Reward Modeling
Distributed Systems
High-Performance Computing
Data Pipelines