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.
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Machine Learning Engineer (Up to £180k + equity) employer: Oliver Bernard
At Oliver Bernard, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through continuous learning opportunities and the chance to work with cutting-edge technologies in a vibrant location. Join us to make a meaningful impact while enjoying a supportive environment that values your contributions.
