Machine Learning Engineer (Up to £180k + equity)

Oliver Bernard; Greater London; On-site; GBP 162,000 - 198,000; Full time

Job summary

Oliver Bernard is partnering with a well-funded London AI startup to hire a Machine Learning Engineer. The role sits between research and production, turning ML prototypes into scalable systems deployed for real customers.

You will own end-to-end ML pipelines, from experimentation to deployment, with emphasis on fine-tuning language models, inference optimization and cost reduction. The role requires 2+ years shipping ML systems, deep learning and LLM experience, and a strong academic

Qualifications

• 2+ years shipping ML systems in a startup or high-ownership environments.
• Strong experience with deep learning and language models.
• Hands-on experience with fine-tuning, RL, distillation or model post-training.
• Sponsorship is available for strong candidates.

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.
• Improve model performance, latency and cost.
• Own ML systems end-to-end from experimentation through deployment.

Skills

Deep learning

Language models

Fine-tuning

RL

Model distillation

System deployment

Education

Bachelor's degree (top university)

Tools

Python

Distributed training

Inference optimization

Data pipelines

LLMs

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
• 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
• 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.

Package

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