This role pays more than
73%
of similar roles. Most pay
$174,600–$244,000
— the shaded band above.
At the midpoint, this role pays about
$242k
versus about
$209k
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
367 open roles
on FindRole.
Listed pay typically runs
$166,400–$249,600
across 367 roles with salary data.
As a Technical Marketing Engineer within the Software Product Management organization for the Data Center GPU Business Unit, you will bridge technical expertise with clear communication to support the customer journey. You will translate internal reference designs into customer-ready technical briefs, deployment guides, and training materials for AMD Instinct powered solutions. Your daily work involves creating enablement assets like whitepapers and pitch decks while delivering technical training on GPU clusters, networking fabrics, power, and cooling for internal teams and external partners. The role requires proficiency in 400G/800G Ethernet, RoCE, leaf-spine topologies, and high-density rack designs. You will solve complex problems regarding the design, deployment, and scaling of large-scale AI datacenters by distilling dense technical information into compelling narratives that highlight performance, scalability, and total cost of ownership for HPC and AI infrastructure.
Translate internal reference designs into customer-ready technical briefs and deployment guides.
Articulate system-level value propositions regarding performance, scalability, networking, power, and cooling to sales teams.
Create "what to say" guidance including sizing recommendations and architectural tradeoffs for customers.
Develop enablement assets such as pitch decks, whitepapers, and competitive positioning materials.
Design and deliver technical training for internal staff and external partners like OEMs and CSPs.
Build modular, reusable training content including slides, diagrams, and labs for global scale.
Provide field feedback to influence future reference architectures and documentation priorities.
Ensure technical accuracy and consistency across all published customer-facing materials.
What we're looking for
A BS in Computer Science, Computer Engineering, Electrical Engineering, or a related field is required.
Experience in technical marketing, systems engineering, solutions architecture, or related roles focused on datacenter infrastructure or AI platforms is preferred.
Strong understanding of GPU-based AI clusters, including scale-up and scale-out architectures.
Hands-on knowledge of datacenter networking including 400G/800G Ethernet, RoCE, leaf-spine topologies, and rail vs. fat-tree designs.
Familiarity with power delivery and cooling for high-density racks, including air and liquid cooling.
Demonstrated ability to translate complex technical content into clear, sales-ready documentation and presentations.
Excellent written communication, presentation, and technical storytelling skills with strong attention to detail.
Experience with modern documentation workflows such as Markdown, Read the Docs, and Jupyter Notebooks is preferred.
GPU Architecture
NVLink
NVL72
AI Inference
System Architecture
Liquid Cooling
Power Delivery
Thermal Management
Rack-scale Systems
Accelerated Computing
CPU/GPU Co-design
GPU Technologies
Accelerated Computing
Neural Networks
Transformer Architectures
Ray Tracing
Real-time Rendering
Linux
Data Science
AI Tools
Hardware Architecture
Game Development
GPU Optimization
Software QA
CUDA-Q
Quantum Computing
Accelerated Computing
AI
MCP
GitHub
API Documentation
LLMs
Claude Code
Codex
Information Architecture
Content Strategy
Benchmark Harnesses