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McGregor Boyall

Principal ML Engineer

London
£80k – £180k/yr
Posted 1 day ago
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Senior Machine Learning Engineer

AI Startup

Location: Fully Remote (Europe)

Salary: £80,000 - £180,000 + Equity

The Role

I'm working with a well-funded, stealth AI company building a next-generation AI assistant designed to help people manage everyday tasks, conversations and workflows.

The product is still pre-launch, making this a genuine 0-1 opportunity to join a small, high-calibre engineering team and build the machine learning systems that will power the product from day one.

They're hiring across multiple levels, from Senior through to Staff Machine Learning Engineers.

Key Responsibilities

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.

P

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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It searches the market for you

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.

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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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Strong

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.

  • Design, build and deploy production machine learning systems
  • Own the full ML lifecycle, from data preparation through to training, evaluation and inference
  • Turn research into reliable, production-ready ML solutions
  • Optimise models for performance, latency, scalability and cost
  • Build robust training and inference pipelines
  • Debug complex production issues using real-world data and signals
  • Mentor engineers and help drive engineering standards across the ML function

Key Requirements

  • Commercial experience building and deploying production ML systems
  • Strong Python software engineering skills
  • Experience training, fine-tuning or deploying modern machine learning models
  • Strong experience with PyTorch and/or JAX
  • Experience building scalable ML infrastructure and inference pipelines
  • Comfortable owning projects end-to-end in fast-moving environments
  • Previous mentoring or technical leadership experience would be advantageous

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Tech Stack

  • Python
  • PyTorch
  • JAX
  • GPU Training
  • LLMs
  • Modern ML Infrastructure

Get in touch for more details - ncarolan@mcgregor-boyall.com

McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.

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“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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Skills

Machine Learning
Python
PyTorch
JAX
LLMs
ML Infrastructure
Model Training
Model Fine-tuning
Inference Pipelines
GPU Training
Software Engineering
ML Lifecycle Management
Technical Leadership
Scalable Systems

Location

London, England, United Kingdom

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