Hardware Technical Analyst
Cerebras is hiring a Hardware Technical Analyst for a remote role open to applicants in United States. Level rates it ; you can apply on Level.
AI in this role
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the Role
We’re looking for a Hardware Technical Analyst with deep expertise in AI hardware or software to produce original research and turn complex technical developments into clear, credible content. You’ll investigate how systems work, test claims through demos and benchmarks, and explain what the results mean for developers and the broader industry.
This is a hands-on individual contributor role combining technical research, experimentation, and writing. You should be as comfortable examining an architecture or building a reproducible test as you are shaping an article and defending its conclusions. You’ll work closely with Developer Relations, Engineering, and New Media to find meaningful stories, validate the details, and help people understand a rapidly changing AI ecosystem.
What You’ll Own
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 Cerebras 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.
Skills and Qualifications
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.
Preferred Experience
Experience combining technical and financial analysis to explain developments in AI infrastructure.
Experience turning conference findings or conversations with technical experts into published research.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.
How we rate this
Hardware Technical Analyst at Cerebras rates 62 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Walk me through how you've used OpenAI in your day-to-day work.
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI Research and OpenAI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new remote AI jobs (Works on AI ●●●○ or higher) by email
One email a week with the new remote AI jobs (Works on AI ●●●○ or higher), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Other roles that work on AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step