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Blankstate

Lead Machine Learning Research Engineer

London
£95k – £140k/yr
Posted about 11 hours ago
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Lead Machine Learning Engineer

Blankstate is a London-based AI infrastructure company. We have pioneered a new SOTA model topology that independently measures interactions. Our architecture is federated and non-retentive.

We are looking for a Lead Machine Learning Engineer who owns the engineering bridge experimentation between deep model research and the production ecosystem we ship. You would run the seam directly: translating research findings into engineering work, regressions into research questions, and production observations back into experimental probes accompanied with our different units.

This is a senior engineering seat with potential mentorship. You work directly with the Chief Data & Analytics Office and the Global Delivery team, with technical autonomy and a direct line into the science. The design space is open, the constraint set is novel, and the architectural choices you make in your first year become the ecosystem the team builds on.

What we look for

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.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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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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.

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Strong

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.

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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.

  • Six years or more building and shipping ML systems that customers used and that you were responsible for end-to-end, from offline metric to user-visible behaviour.
  • Strong on at least one of: federated or edge ML systems; evaluation and orchestration; simulation-based testing and benchmarking; compiler-style configuration systems, or anything in that family.
  • An instinct for making things simpler alongside making them more capable. We hire people who reduce complexity, not just add to it.
  • Comfortable in both owning a multi-surface engineering programme and deepen one component.
  • The kind of senior who unblocks others by default.
  • Fluent in PyTorch and modern serving infrastructure; comfortable engaging with the front-end team on Rust and React adjacent product work even if not writing it.

Nice to have

  • Privacy-preserving ML in production: differential privacy, federated averaging, secure aggregation, on-device inference at scale.
  • Evaluating modern models under realistic constraints: tool use, multi-step reasoning, memory, parallel execution.
  • Open-source contributions to evaluation harnesses, simulation frameworks.
  • A published research idea you shipped as customer-visible product behaviour.

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What we offer

  • Base salary of £95,000 – £140,000 annually (dependent on experience).
  • Meaningful share-pool participation in a UK-based deeptech company.
  • Pension and standard UK benefits.
  • A conference budget that funds at least one tier-1 venue per year as a co-author or first-author submission.
  • Full access to Blankstate's research compute. No notebook-only roles.
  • A direct line to the cofounder, the operational research-leadership seat for the next two years, and a clear path to grow alongside the Scientific Director once that seat is filled.
  • Flexible working from our London Research Unit next to Hyde Park, with a culture that rewards depth and rigour over performative output.
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Skills

PyTorch
Federated Learning
Edge ML
ML Orchestration
Simulation-based Testing
Compiler Configuration Systems
Rust
React
Differential Privacy
Secure Aggregation
On-device Inference
Model Evaluation
MLOps
Deep Learning Research
System Architecture
Technical Mentorship

Location

London, England, United Kingdom

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