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Machine Learning Engineer (Production ML Systems)

Oliver Bernard United Kingdom
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AI Summary

Seeking a Machine Learning Engineer to bridge research and production for a London-based AI startup. This role involves taking ML research from prototype to deployment, optimizing LLMs, and building scalable inference systems. Requires 2+ years of shipping ML systems, strong deep learning/LLM experience, and Python engineering skills.

Key Highlights
Build and optimize production ML systems for a well-funded AI startup.
Focus on taking research ideas to reliable, scalable deployment.
Opportunity to work with LLMs, large-scale modeling, and real-world decision support.
Key Responsibilities
Take new ML research from prototype through to production
Fine-tune, post-train and distil language models
Build and optimise inference systems at scale
Design data pipelines for large, messy real-world datasets
Improve model performance, latency and cost
Own ML systems end-to-end from experimentation through deployment
Technical Skills Required
Python LLMs Deep Learning
Benefits & Perks
Up to £180,000 salary
Equity
Visa sponsorship available
Nice to Have
RL
model distillation
distributed training
inference optimisation
data pipelines

Job Description


Machine Learning Engineer | Up to £180k + Equity | London, 5 Days Onsite


We're working with a well-funded London AI startup building complex production ML systems for major global organisations.


The business is tackling a technically difficult problem that sits across large-scale modelling, LLMs and real-world decision support.


They've already secured strong commercial traction, are backed by leading investors, and are now expanding the engineering team around the core ML platform.


This role is focused on taking ambitious research ideas and turning them into reliable production systems.


The Role


You'll sit between research and engineering, owning the path from ML prototype through to deployment, optimisation and scale.


Responsibilities


  • Take new ML research from prototype through to production
  • Fine-tune, post-train and distil language models
  • Build and optimise inference systems at scale
  • Design data pipelines for large, messy real-world datasets
  • Improve model performance, latency and cost
  • Own ML systems end-to-end from experimentation through deployment


Requirements


  • 2+ years shipping ML systems in a startup or high-ownership environment
  • Strong experience with deep learning and language models
  • Hands-on experience with fine-tuning, RL, distillation or model post-training
  • Strong Python engineering skills
  • Experience deploying models used by real customers, within a startup or fast growing scale-up environment.
  • Strong academic pedigree with a bachelors degree from a top university.


Sponsorship is available for strong candidates.


Tech

Python, LLMs, fine-tuning, RL, model distillation, distributed training, inference optimisation, data pipelines.


Location

London, 5 days per week onsite.


Package

Up to £180,000 depending on experience plus equity.


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