Summary
What you’ll impact
The Associate AI Hardware Analyst conducts original research on AI hardware and software, turning complex technical developments into clear, evidence‑based content. Using AI accelerator architectures, benchmarking tools, and AI development frameworks, they build reproducible demos and performance evaluations. They produce technical articles, research reports, and benchmark analyses that explain system trade‑offs, performance metrics, and industry impact. Collaboration with developer relations, engineering, and media teams, as well as presenting at conferences, ensures the findings are accurate and engaging.
Responsibilities
What you'll do
- Original research: Analyze AI hardware, software, infrastructure trends, and industry announcements. Identify meaningful developments and differentiated story angles, and develop a point of view supported by evidence.
- Technical writing: Write articles and research that make complex ideas accessible without sacrificing accuracy. Explain how systems work, what is new, and why it matters.
- Demos and benchmarks: Build demos and run reproducible benchmarks to test claims, investigate performance, and explore tradeoffs. Document your methodology, assumptions, and limitations.
- Evidence and analysis: Synthesize technical and financial information from primary sources, expert conversations, and hands-on work into clear insights. Evaluate source quality and revise conclusions when the evidence changes.
- Technical collaboration: Partner with Developer Relations, Engineering, and New Media to develop technically grounded content, validate conclusions, and incorporate expert and editorial feedback.
- Industry engagement: Represent the organization at industry conferences and turn relevant findings and conversations into useful research and content.
- Research workflows: Use AI tools to accelerate research, coding, and writing while independently verifying sources, results, and claims.
Requirements
What you’ll bring
- 2–3 years of experience in hardware, AI software, technical research, or a similarly analytical environment.
- A strong portfolio of externally published technical writing, research, or other substantive technical content.
- Deep expertise in AI hardware or software, including the architectural and system tradeoffs that affect performance and practical use. Your strength may be in hardware architectures, compute, memory, and interconnects, or in models, inference, and AI application workflows.
- Demonstrated experience building demos or running benchmarks, with the ability to explain your personal contributions, methodology, and results.
- Clear technical writing and communication. You can explain complex mechanisms, support a point of view with evidence, and make the significance clear to your audience.
- Strong research judgment. You can evaluate sources, distinguish evidence from assumptions, design fair comparisons, and communicate limitations honestly.
- Good editorial judgment about what makes technical content original, useful, and engaging.
- The ability to learn unfamiliar technical subjects, collaborate with experts, incorporate critical feedback, and deliver under a deadline.
- Strong familiarity with AI tools and sound judgment about where independent verification is necessary.