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C&D Talent Advisory - Academy

Senior ML Engineer | London

Nottingham
£100k – £150k/yr
Posted about 20 hours ago
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We only work with real companies hiring for live positions. Every opportunity on our platform is an active search. If there's a strong match, we'll guide you through the process. If not, we won't ignore you.

About The Company

Our Client is a venture-backed AI startup building a next-generation foundation model to enable fully autonomous software delivery for embedded control systems.

This is an opportunity to join at an early stage, work directly with the founders, and help shape a technology designed to redefine how software is built, optimized, and deployed.

Location: London, United Kingdom (Remote with monthly office visits, ideally onsite)

Employment Type: Full-time

Level: Mid-Senior Level

Compensation: £100,000-£150,000 + Equity (Share Options)

Work Authorization: Existing UK work authorization required

About The Role

We're looking for a Senior Machine Learning Engineer (Foundation Models) to lead the development, optimisation, and production deployment of our next-generation foundation model.

This is a deeply technical, hands-on role where you'll:

  • Architect large-scale ML systems
  • Optimise distributed training and inference
  • Build GPU-accelerated infrastructure
  • Work directly with founders to solve complex engineering challenges

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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If you're excited by cutting-edge AI research, production-scale machine learning, and building systems that push the limits of modern deep learning, we'd love to hear from you.

What You'll Do

Foundation Model Development

  • Lead the research, development, and deployment of large-scale foundation models
  • Define long-term technical strategy for high-performance ML systems
  • Build scalable training and inference infrastructure
  • Own model quality, performance, and reliability

ML Infrastructure & Optimisation

  • Optimise distributed training and inference pipelines
  • Design GPU-accelerated systems, including custom CUDA kernels when needed
  • Profile and optimise data pipelines, training loops, inference, and deployment
  • Build internal tooling, benchmarking systems, and evaluation frameworks

Architecture & Collaboration

  • Design scalable ML infrastructure and solution architectures
  • Evaluate and implement state-of-the-art ML technologies
  • Work closely with founders to translate product goals into technical roadmaps
  • Drive engineering excellence across the ML platform

What We're Looking For

Must Have

  • Extensive experience designing and building large-scale foundation models
  • Strong Python and CUDA C/C++ expertise
  • Deep knowledge of PyTorch (preferred) or another major deep learning framework
  • Experience optimising and debugging deep learning models
  • Experience with distributed training and large-scale inference
  • Experience building ML systems on AWS, Azure, or GCP
  • Strong GPU optimisation experience
  • Experience building production ML infrastructure
  • Excellent system design skills
  • Delivery-focused mindset with strong ownership
  • Comfortable solving ambiguous, high-impact problems
  • Able to work onsite in London or visit the office at least once per month

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Nice to Have

  • Experience with Mixture of Experts (MoE) or State Space Models
  • Custom CUDA kernel development
  • ML systems operating under strict production SLOs
  • Experience building internal ML tooling and benchmarking frameworks
  • Startup or research lab experience shipping foundation models
  • Experience scaling distributed GPU clusters

What We Offer

  • £100,000-£150,000 salary
  • Meaningful equity (Share Options)
  • Opportunity to build a first-of-its-kind foundation model
  • Direct collaboration with founders
  • No take-home assignments or live coding interviews
  • Transparent, low-ego engineering culture
  • High ownership and technical autonomy
  • Office-first environment with flexibility for exceptional candidates

If you want to help build the next generation of foundation models and solve some of the hardest ML problems in production, we'd love to hear from you...

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Skills

Machine Learning
Python
CUDA C/C++
PyTorch
Deep Learning
Distributed Training
Inference
AWS
Azure
GCP
GPU Optimisation
System Design
Engineering Excellence
Model Quality
Performance
Reliability

Location

Nottingham, England, United Kingdom

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