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Xcede

Lead Machine Learning Engineer

London
Posted 1 day ago
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Lead Machine Learning Engineer – Retail

x2 days per week in a central London office (hybrid)

About the Company

We’re working with a fast-scaling AI organisation that partners with large product and platform-led businesses to deliver machine learning systems that support personalisation, demand forecasting, and operational resilience. Their work helps clients enhance customer experience, optimise fulfilment and logistics, and make smarter, data-driven decisions.

This is a senior-level technical role with plenty of scope to shape the architecture, tooling, and delivery practices across impactful applied AI projects.

What You’ll Be Doing

  • Lead the design and development of robust machine learning platforms that power core business functions across multiple client environments
  • Set technical strategy across projects and drive execution on model development, deployment workflows, and infrastructure
  • Collaborate with engineers, product teams, and stakeholders to translate high-level objectives into scalable ML solutions
  • Build shared tools and frameworks that support consistency and reusability across the engineering function
  • Guide project scoping and delivery plans while helping define best practices around ML system design
  • Mentor engineers at varying levels and contribute to hiring, capability building, and tooling decisions
  • Help clients understand trade-offs and solution architecture, acting as the senior point of technical contact throughout delivery

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

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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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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.

What They’re Looking For

  • Strong experience leading end-to-end ML engineering projects, ideally with exposure to customer-centric, high-traffic environments
  • Proficiency in Python and hands-on experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn
  • Familiarity with cloud-based deployment workflows and infrastructure management (e.g. AWS, Azure, or GCP)
  • Real-world experience working with Docker, Kubernetes, and production ML pipelines
  • Strong communication skills and comfort engaging across technical, commercial, and executive teams
  • A pragmatic and detail-oriented approach to balancing experimentation with reliable, scalable delivery

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Get help applying for this job

If this role interests you and you would like to find out more (or find out about other roles), please apply here or contact us via niall.wharton@Xcede.com (feel free to include a CV for review).

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Skills

Machine Learning Engineering
Python
PyTorch
TensorFlow
Scikit-learn
AWS
Azure
GCP
Docker
Kubernetes
ML Pipelines
System Architecture
Technical Strategy
Mentoring
Stakeholder Management

Location

London, England, United Kingdom

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