Technical Content Lead

Normal Computing | Build with Us

Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), and London.

Your Role in Our Mission

We are hiring a Technical Content Lead who combines original technical writing with the depth of an industry analyst. The challenge is to understand Normal Inference Systems in the context of industry developments, customer needs and expectations, and turn that understanding into accurate, relevant content. Your analysis will guide what we publish, how we explain Normal's advantages and how we answer the questions engineers and customers bring to the technology.

You will work directly with scientists, researchers and engineers, read the underlying papers and results, and learn challenging new science every day. You will write blog posts, social copy, research stories, technical essays and evaluation materials, while helping engineers and researchers develop their own content. Alongside the hardware, you will own research communications for Normal's frontier applied AI research program, which develops AI methods for silicon design and verification.

This is a senior individual-contributor role reporting to the Head of Communications and embedded with Engineering. You will be the subject-matter expert on technical content, progress and the hardware roadmap. Original technical analysis, writing and editorial partnership with technical experts are the core of the role. You will also advise and co-create across the website, explainer videos and technical design assets with colleagues in editorial, product marketing, media relations, brand design and social production.

Responsibilities

• Write technical content. Write original blog posts, social copy, research stories, technical essays, whitepapers and explainers about Normal's hardware and applied AI research. Develop the substance and argument directly with scientists, researchers and engineers, lead pieces through expert review, and work with editorial colleagues on framing, voice and publication. Draft technical documentation that supports research communication and customer evaluation.

• Strengthen shared content. Edit, write and co-author external-facing content with technical experts, shaping arguments, strengthening explanations and supporting expert review. Polish presentations and customer collateral for their intended audiences while maintaining technical accuracy. Contribute original writing and technical judgment to website content, explainer videos and technical design assets with Communications and Marketing colleagues. Work with product marketing to explain Normal's specific advantages using industry insight and verified technical evidence.

• Translate industry and customer insight into content. Research AI infrastructure and semiconductors through primary sources, expert discussions and customer feedback. Compare architectures, workloads, benchmarks and competing products, and assess how technical tradeoffs affect workload economics and customer value. Use this understanding of industry trends and customer expectations to plan, write and update content, choose the questions worth explaining, and keep our arguments relevant to the people evaluating the hardware. Work with product marketing on positioning and ensure the website, technical stories and customer materials reflect both verified product progress and changes in the market.

• Embed with Engineering. Join engineering, silicon and research team meetings and roadmap discussions to support their content needs and understand their work in depth. Resolve open technical questions with the relevant experts. Brief Communications and Marketing regularly on verified progress, technical definitions, performance, configurations and roadmap or timeline changes. Flag unresolved questions and decisions that need wider input, and turn verified changes into updates across technical writing, the website, customer collateral, videos and design assets. Distinguish measured results from targets and projections. Keep confidential and unreleased information internal until approved for external use.

• Explain technical performance. Work with Engineering to interpret benchmarks and results, develop useful comparisons and explain the performance of Normal Inference Systems to technical and commercial audiences.

• Build customer materials. Develop the technical substance of evaluation materials, decks, briefs and FAQs with colleagues leading product marketing and customer work. Explain system capabilities, integration requirements and workload economics in ways that help customers evaluate the product.

• Make answers findable. Turn recurring customer questions into useful, searchable technical explanations with colleagues in editorial and product marketing. Connect answers to relevant research and evaluation materials, and keep them current as systems and capabilities change.

• Explain the evidence. Develop diagrams, plots and, where useful, reproducible examples or notebooks with internal experts and external collaborators. Give readers and colleagues a clear basis for understanding and checking technical claims.

• Learn from the field. Join relevant research, product and customer discussions to understand workload needs, evaluation criteria and recurring questions. Use lab sessions, roadshows and account feedback to identify stories worth developing and improve the usefulness of our content.

• Ensure technical accuracy. Resolve open questions with the right experts and keep review moving against deadlines. Maintain consistent company language and product naming, and update published content when new evidence changes the answer.

What We Are Looking For

• Technical depth and original writing. A portfolio of substantial technical work you authored and can explain in depth, with evidence of consistently publishing strong work at pace. Show us original analysis of architectures, technical results or industry developments, including how you checked the evidence and reached your conclusions. Deep-tech journalism, technology or equity research, and equivalent in-house writing and editing experience are especially relevant. Research, engineering and technical marketing backgrounds can also qualify with the same evidence of analytical depth, original writing, editorial judgment and delivery. You can engage in substantive discussions with technical leads and develop original writing from primary sources; the depth and quality of your work matter more than a particular degree, employer or title.

• Domain depth and learning speed. The ability to go deep enough into subjects such as AI inference, computer architecture, semiconductors or computational physics to write credibly and precisely. You can build understanding from primary sources and expert conversations, identify gaps in your knowledge and learn challenging new material quickly.

• Technical reasoning. You can read a research paper, question a benchmark and explain a mechanism in your own words. You know when a conclusion depends on an assumption, what makes a comparison valid and which question requires another measurement.

• Working with evidence. Comfort with benchmark data, plots and technical diagrams, and with code or notebooks when they are part of the underlying work. Experience creating runnable examples or reproducible technical artifacts is useful.

• Audience judgment. You can write for a domain expert and adapt the same substance for a customer or executive with clarity and precision. You think about the visual explanation alongside the prose.

• Cross-functional collaboration. You earn the trust of researchers and engineers and bring your own thinking to projects across the team. You share work early, invite contributions and help colleagues strengthen and amplify their content. You can turn new developments into publishable work quickly, manage expert reviews and meet a regular publishing cadence while protecting technical accuracy.

• Travel readiness. Willingness to travel for team collaboration, lab work, customer evaluations and relevant industry events.

Equal Employment Opportunity Statement

Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.

Accessibility Accommodations

Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at [email protected].

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