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AI System Architect

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Role Overview
I’m working with a cutting-edge hardware manufacturing startup developing technology which could transform the economics of AI. This is a team pioneering an AI accelerator for data centres to perform computation at much greater speeds whilst consuming far less energy than other approaches. They’re bringing technology to market that is pushing boundaries and changing how AI scales globally.
This is an exciting opportunity for an AI System Architect looking to join a team that is redefining how the world computes.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What They’re Looking For
- Deep AI/ML expertise - transformers, CNNs, recommender systems, and strong intuition for compute + memory behaviour
- Architecture experience – designing systems or chips for ML training/inference
- Performance modelling - roofline analysis, bandwidth modelling, cycle‑level estimation
- Hardware–software fluency - ISA design, compiler interfaces, runtimes, and datapath microarchitecture
- Industry background - experience at AI‑chip startups or major AI‑hardware teams (TPU, MTIA, Trainium, Dojo, etc.)
- Compiler‑stack familiarity - MLIR, XLA, TVM, Triton and how they shape hardware choices
- Influence through writing - strong written specs and data‑driven decision‑making


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Why Consider It
- Work on frontier problems in AI‑driven silicon design
- AI‑first culture where hardware exists to maximise model performance
- High impact from day one on product direction
- Competitive compensation with salary, equity, and benefits
- Flexible working arrangements
Please contact Chris Amison for more information.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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