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AP Executive - Global Executive Search Agency

Machine Learning Engineer (various levels), AI - London

London
Posted 1 day ago
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Machine Learning Engineer (various levels), AI - London

About the Opportunity

Our client is a well-capitalised, early-stage technology company developing an advanced AI-driven product for consumers. The engineering challenge is significant: the system must perform complex, multi-step reasoning, maintain context over extended interactions, and operate reliably in production despite the inherent unpredictability of large models.

The organisation is deliberately lean - a small group of senior, high-calibre engineers who move quickly, make decisions collectively, and hold a high bar for both quality and pace. The mission is to deliver a product experience that feels genuinely different from what's currently on the market.

The Roles

Our client is looking to hire multiple profiles into their ML Technical staff. As a Member of Technical Staff, Machine Learning, you will build core ML components and work directly on production systems from day one - gaining first-hand exposure to how large-scale ML behaves outside a research setting. This role suits engineers who want to build strong systems judgement through shipping, debugging, and iterating on real-world ML, alongside more senior colleagues.

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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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  • Build and improve ML components spanning data, training, evaluation, and inference
  • Fine-tune and adapt models as part of larger production systems
  • Implement evaluation and testing frameworks to understand model behaviour
  • Contribute to data pipelines covering both real-world and synthetic data
  • Debug model issues, performance problems, and production incidents
  • Ship improvements iteratively, guided by real user feedback
  • Work closely with senior ML engineers and product teams
  • Operate comfortably within the constraints of a live production system - latency, cost, reliability, and safety all matter simultaneously

What Good Looks Like in This Role

  • Production ML models meet expected accuracy, latency, and reliability targets
  • Production issues are identified quickly, debugged effectively, and resolved at the root cause
  • Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable
  • Works effectively across engineering, product, and research to deliver reliable ML-powered features
  • Improvements to models and systems are driven by real-world signals and measurable outcomes

Technical Environment

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  • Python
  • PyTorch / JAX
  • Production ML systems running on GPU infrastructure

Candidate Profile

  • Strong foundations in machine learning and modern neural network architectures
  • Some hands-on experience training, fine-tuning, or deploying ML models
  • Comfortable writing production-quality code and picking up new tools quickly
  • Curious, coachable, and keen to learn from real systems in production
  • Able to work through ambiguity with guidance, growing ownership over time
  • A natural bias toward shipping, iteration, and continuous improvement

To apply or discuss this role further please send your CV to Don Fletcher via don.fletcher@ap-executive.com

AP Executive are working with a well capitalised early stage AI firm looking to expand their ML Team.

AP Group is acting as an introductory service in relation to this vacancy. By submitting your CV for consideration, you are consenting to its retention for the purpose of securing you work. Any information you provide to AP Group and its subsidiaries will be subject to the protection of Data Protection Laws, our policy for which can be found at https://www.apgroupglobal.com/privacy-notice/

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Skills

Machine Learning
Neural Networks
Python
PyTorch
JAX
Data Pipelines
Model Evaluation
Debugging
Production Systems
Continuous Improvement
Model Fine-Tuning
Real-World Signals
Collaboration
System Judgement
User Feedback
Production Quality Code

Location

London, England, United Kingdom

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