Founding Researcher
First seen by Alion on Oct 26, 2026.
AI is centralised. A handful of companies control the models, the compute, and — by extension — the world’s data. Unlike past technologies, AI is trained on the sum of human knowledge and decisions. Its centralisation is more consequential than anything we’ve seen before — reducing sovereignty, eroding privacy, and limiting accessibility.
At EXO, we’re building the alternative. We make it possible to run AI locally — from a single MacBook to clusters of thousands — giving people and organisations back sovereignty, privacy, and control.
Who we are- SF culture, but in London (we are all in-person in our office near Tower Bridge): we all want to build something great.
- Open‑source repo among the fastest‑growing in AI, with 30K+ stars and 1M+ downloads.
- Enterprise demand is so strong that we’re turning customers away.
- Small, elite team in London with exceptional talent density (Previously Oxford/Cambridge, IMO, Jane Street).
- Now we’re hiring exceptional researchers to build with us.
We are building an AI stack from the ground up, optimised for consumer hardware — from the models to the distributed algorithms, scheduling, and orchestration.
On consumer hardware, we face higher memory‑to‑FLOPS ratios, unreliable connections as devices go offline and move networks, and higher network bandwidth‑to‑FLOPS ratios than datacenter GPUs.
As a Founding Researcher, you will drive research that unlocks performance on Apple Silicon: bs=1 attention paths and kernels, MoE routing for unified memory, quantization strategies, topology‑aware scheduling, and KV transport — turning promising ideas into prototypes that deliver measurable product wins.
Who we’re looking for- PhD in AI/ML or 3+ years as a researcher at a top lab/company.
- Strong ML fundamentals and systems pragmatism; comfortable with kernels, profiling, and memory models.
- Builder mindset: write production‑quality code; measure; iterate.
- Mentorship: uplift juniors; bring structure and clarity to research.
- Writing and clarity: produce crisp memos and reproducible experiments.
We’re in‑person in London. The culture is intense, collaborative and there is constant learning.
Tech stack- Python — core orchestration + ML
- Rust — networking, exposed to Python via FFI
- C++ — Apple MLX core
You don’t need to know all of these upfront. The ability to learn quickly and reason from first principles matters more.
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