below marketmost similar roles pay hereabove market
This role pays more than
75%
of similar roles. Most pay
$186,075–$239,062
— the blue band above.
At the midpoint, this role pays about
$242k
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 Technical Marketing Engineer – Datacenter GPU Clusters & Networking joins the Software Product Management organization within the Data Center GPU Business Unit. This role involves bridging deep technical expertise with clear communication to help customers design, deploy, and optimize AMD Instinct-powered GPU clusters and networks for HPC and AI solutions. Key responsibilities include translating internal reference designs into customer-ready technical briefs, creating sales enablement assets like whitepapers and pitch decks, and delivering technical training for internal teams and external partners. The position requires proficiency in GPU-based AI clusters, 400G/800G Ethernet, RoCE, leaf-spine topologies, and power and cooling designs for high-density racks. Candidates must use tools like Markdown, Read the Docs, and Jupyter Notebooks to produce high-quality documentation and training content.
Translate internal reference designs into customer-ready technical briefs, deployment guides, and reference architectures.
Articulate system-level value propositions regarding performance, scalability, networking, power, and cooling for AI data center customers.
Develop "what to say" guidance including sizing recommendations, architectural tradeoffs, and design best practices for sales teams.
Create enablement assets such as pitch decks, whitepapers, FAQs, and competitive positioning for GPU cluster solutions.
Design and deliver technical training for internal teams and external partners on GPU clusters and networking fabrics.
Build modular, reusable training content including slides, diagrams, labs, and recordings for global scale.
Provide structured feedback from the field to influence future reference architectures and documentation priorities.
Ensure technical accuracy and consistency across all published customer-facing materials and documentation.
What we're looking for
BS in Computer Science, Computer Engineering, Electrical Engineering, or a related field required.
MS or PhD is a plus (preferred).
Experience in technical marketing, systems engineering, solutions architecture, or a related role focused on datacenter infrastructure or AI platforms (preferred).
Strong understanding of GPU-based AI clusters, including scale-up and scale-out architectures (preferred).
Hands-on knowledge of datacenter networking including 400G/800G Ethernet, RoCE, leaf-spine topologies, rail vs. fat-tree designs (preferred).
Familiarity with power delivery and cooling for high-density racks, including air cooling, liquid cooling, and rack-level power design (preferred).
Demonstrated ability to translate complex technical content into clear, sales-ready documentation and presentations (preferred).
Experience working with OEMs, ODMs, or cloud service providers is a plus (preferred).
Remote (Santa Clara, CA)105 days ago
$160,000–$253,000
GPU Architecture
NVLink
NVL72
AI Inference
System Architecture
Liquid Cooling
Power Delivery
Thermal Management
CPU/GPU Co-design
Accelerated Computing
Rack-scale Systems
GPU Technologies
Neural Networks
Transformer Architectures
GPU-accelerated Computing
Data Science
Real-time Rendering
Ray Tracing
Linux
Command-line Tooling
AI Tools
Software QA
PC Hardware Architecture
Model Inference
Performance Testing
Game Development
GPU Optimization