
Efficient Computer is rethinking computing from the ground up to solve one of AI's biggest challenges: energy. Our Fabric architecture delivers a 10–100x improvement in energy efficiency for general-purpose computation, including AI, while supporting familiar programming languages and software frameworks—unlocking new possibilities for autonomous machines, intelligent infrastructure, wearables, and space systems. With our first processor, Electron E1, now shipping in volume and more than $97 million in Series B financing recently announced, we're accelerating customer deployments and scaling our architecture to data center performance. Join us to build the hardware and software that bring intelligence wherever it's needed and help shape the next generation of computing.
Efficient Computer is seeking a Technical Content Writer who enjoys figuring out how things work and helping other people understand them. You have an engineering background, and writing is the part of the job you want to spend more time doing.
At Efficient, you will help engineers, product managers, and technology leaders understand what a different processor architecture could make possible for their products. That might mean adding a new feature, running more processing on the device, or extending battery life. Your job is to explain how it works, and show the results.
Much of your work will start with our applications and engineering teams. You will turn their customer applications, benchmarks, and reference designs into useful content for people evaluating our technology. You will also spend time with the hardware yourself: bringing up an Evaluation Kit (EVK), compiling real code with the effcc Compiler, and taking measurements when you need to understand or explain a result. Whether you are working from a teammate’s findings or your own, readers should have enough detail to reproduce the results.
We want our content to be as useful and reliable as the engineering behind it. We publish measured results that we can reproduce, and we explain the conditions behind them. You will work directly with our architecture, compiler, applications, and product teams and have access to the hardware. If a claim needs more work before we can stand behind it, we expect you to say so.
We offer a competitive base salary for this role, generally ranging from $120,00-180,000, plus a 10% annual bonus, meaningful equity, and comprehensive benefits. Final compensation will depend on experience, level, and location, with flexibility for the right candidate.
Why Join Efficient?
Build what's next. At Efficient, you'll tackle big challenges with room to take ownership and make an impact. We back you with competitive pay, equity, a 401(k) match, company-paid benefits, paid parental leave, and flexibility—plus opportunities to grow your skills and career as we scale.

Efficient is building the world’s most energy-efficient general-purpose processor by combining ultra-efficient hardware with an intuitive, developer-friendly compiler and software stack that unlocks 10–100× efficiency gains across every part of an application, including AI. Efficient was founded in 2022 to commercialize a breakthrough in efficient computation developed over nearly a decade by a team of world-leading computer architects. Efficient's world-class team has produced two silicon implementations of the Fabric architecture: the Electron E0, a prototype system-on-chip, and the Electron E1, the first silicon product. With Efficient's cutting-edge effcc Compiler and software stack, the Electron E1 processor has been delivered to customers as of mid-2025, ramping to large-scale volume and distribution in 2026. Efficient already has customer traction in areas such as physical AI for infrastructure and automation, space and defense, automotive, and consumer products. Efficient's technology scales from tiny “beyond the edge” devices to large-scale robotics, autonomy, edge cloud, and datacenter applications—enabling widespread adoption across multiple industries and positioning Efficient as the solution to the energy problem across all of computing.