Careers
We're a small, focused team working on genuinely hard problems in AI compression and on-device inference. If you want your work to matter — in clinics, in the field, on devices that have never had access to AI — come build with us.
Our Mission
Sustainable means intelligence that requires dramatically fewer resources — cost-effective, environment-friendly, and able to run in places where the cloud has never reached. The average AI inference wastes 99% of its compute. We're building the architecture that eliminates that waste, one compressed model at a time.
That mission shapes everything about how we work: small team, high ownership, zero theatre. Every line of code, every experiment, every product decision connects back to getting intelligence into the hands of people who need it most.
Remote-first, always
We didn't go remote because of a pandemic. We went remote because the best people for this work aren't all in one city. Our team spans the UK and India today, with plans to keep growing globally. We communicate asynchronously by default, document decisions in writing, and treat timezone flexibility as a feature — not a workaround.
There are no mandatory stand-ups at inconvenient hours. No "camera on" meetings for the sake of it. You're trusted to work in the way that makes you most effective.
Async by default
Work at your peak — not at someone else's schedule.
No performative presence
Output over optics. We measure what you build, not when you're online.
Written culture
Decisions are documented, context is shared, nobody is left out of the loop.
Annual in-person retreats
We meet in person to build relationships — not to work through a slide deck.
Perks & benefits
Travel stipend
Annual budget for team meetups and offsites in person.
Wellness allowance
Gym, therapy, meditation — whatever keeps you at your best.
Learning budget
Courses, books, conferences — no approval forms, just learn.
Software & tooling
Full access to the tools you need — we don't nickel-and-dime on software. Plus, a generous amount of Claude credits.
Competitive salary
Benchmarked to top-tier tech salaries in your local market.
Distributed-first culture
No performative presence. We hire globally and work asynchronously.
Open roles
We're a small team hiring carefully. Every person shapes the company.
We're compressing intelligence down to what matters. If you find it absurd that a 70B-parameter model needs a server rack to answer a question — and you want to do something about it — this role is for you.
You'll work at the intersection of theoretical insight and production reality: designing compression algorithms, optimising on-device inference kernels, and shipping models that run on the hardware humanity actually has — not the hardware in a cloud data-centre.
Our compression technology achieves upto 60x size reduction while preserving model quality. You'll push that further, contribute to our Fern on-device LLM, and explore world-model architectures that reason causally without requiring internet-scale compute.
What you'll do
What we look for
Stack / tools
Most "AI products" are wrappers around API calls. We're building something different: a runtime for composable AI agents that works completely offline. If the boundary between product, platform, and infrastructure excites you rather than intimidating you, keep reading.
The Everyday Series is our suite of no-code and low-code tools that let individuals and teams build, share, and run AI agents — no cloud account required. You'll shape both the product people see and the infrastructure that makes it possible.
This is a full-stack role, but "full-stack" here means everything from CLI ergonomics to real-time streaming UI to the agent runtime that runs on a device with no internet. You'll have direct influence on what we ship and how users experience AI for the first time without a dependency on the cloud.
What you'll do
What we look for
Stack / tools
Our technology only matters if it runs in the places that need it most — a clinic with no broadband, a submarine, a regulated government network. You're the engineer who gets it there. Part integration specialist, part solution architect, part trusted partner to the customer.
Forward Deployed Engineers at Antelligent sit at the edge between our core platform and the real-world environments where it gets deployed. You'll work directly inside customer environments — from defence labs to hospital networks to industrial facilities — understanding their constraints and doing whatever it takes to make the deployment succeed.
This role is deliberately hard to categorise. On any given week you might be writing a custom integration layer, advising a customer's infrastructure team, debugging a model loading issue on a proprietary OS, or writing the internal runbook that makes the next deployment twice as fast. You'll feed everything you learn back to core engineering so the platform gets better with every deployment.
What you'll do
What we look for
Stack / tools
We're pre-commercial on technology that compresses AI models by up to 60× — and we're looking for someone who can walk a CTO through why that matters and close the deal. If you love the moment when a technical customer finally sees the thing you've been building, this is your role.
This is a founding sales hire. You'll own the full commercial pipeline: identifying design partners, running technical evaluations, negotiating pilots, and converting them into long-term contracts. You're selling compression-as-a-service, on-device models, and hardware licensing — to enterprises, research labs, and government bodies who need AI to work where the cloud doesn't reach.
You'll work directly with the founders and engineering team. There's no playbook yet — you'll write it. That means you need to be comfortable in a boardroom and a Jupyter notebook, and know the difference between a quantised model and a distilled one.
What you'll do
What we look for
Stack / tools
How to apply
We think harrowing application forms are a waste of everyone's time. If one of the roles above made you lean forward, we want to hear from you — in your own words.
Drop us a line at [email protected] telling us what excites you about the role and why you'd be a great fit. Attach your CV if you'd like, or share a link to your LinkedIn or GitHub profile — whatever tells your story best.
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A quick chat
If there's a match, we'll set up a relaxed 30-minute call — no whiteboard, no trick questions.
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A small task
A short, paid take-home that reflects real work. We respect your time and compensate accordingly.