Engineer Journalist

Turn research on models, inference, and hardware into work that helps engineers understand the stack they rely on.

About Gradiated

Gradiated is a research lab focused on inference. We co-design software and hardware for efficiently serving open-weight models.
Our goal is to maximize intelligence per joule. We work across model behavior, software, systems, and silicon to find better ways to run models.
We start by thinking about the model as a mathematical function, and map that out onto hardware and then build software on top of that which is custom to each model. This maximises performance and removes wasted abstractions.
We are early. Be the founding content and marketing person in the company.

Software engineers increasingly rely on models, inference systems, and hardware for almost all of their day-to-day work, but rarely get a clear view of how those systems work. We think they should. Knowledge is power.
Our research team produces whitepapers about the inference stack. You will be the translation layer between this work and regular full-stack software engineers who want a deeper understanding of what they are building on top of.

Work with our researchers as their work develops, not only after a paper is finished.
Turn our whitepapers into articles that teach full-stack engineers the concepts, evidence, and practical consequences of the research.
Read new model papers, then explain the architecture, training process, evaluations, strengths, weaknesses, and implications for inference.
Build small experiments, benchmarks, diagrams, and code examples when they make an explanation more useful or more honest.
Develop a distinct technical reputation for Gradiated that engineers trust.

You have real software engineering experience and can investigate a technical claim in papers, code, traces, and benchmarks rather than repeating its summary.
You write clearly and precisely, and you care about teaching rather than sounding clever.
You can explain technical depth without removing the caveats, evidence, or uncertainty that make it trustworthy.
You are curious enough to follow a question across models, training, inference software, systems, and hardware.
You know how to interview technical people, challenge assumptions, and find the question that unlocks an explanation.
You have writing, teaching, or explanatory work that shows how you think. It does not need to have been your job title.

You don't already read lots of whitepapers.
You're scared about learning about hardware if you're not in that world already.
You haven't truly been an engineer building production systems before.
You need lots of handholding.

We like to experiment a lot and do the hard thing even if it's likely to fail.
We work in the office several days a week. We value working in person to solve hard problems, but are also flexible, some of the team work abroad for short periods.

The base salary is £130,000-£160,000, with significant equity on top of that.
We pay at the top of the market because talent density is what allows us to build the most efficient inference. We want a small team of exceptional people who have fun solving hard problems together.

We get together in person and talk through the problems we will work on.
A paid in-person working session, so we can get to know you and you can meet the team.
References and an offer decision.

Apply

If this sounds interesting to you, we'd like to hear from you. There's no need to prepare anything, we'll start with a conversation.