Senior / Lead Machine Learning Engineer - Time-Series, Customer Behaviour, ML systems, feature stores, MLOps
London Hybrid | £100,000 – £120,000 + Equity
This is a genuinely interesting opportunity for someone who enjoys solving large-scale, real-world machine learning problems rather than purely experimental work.
The team is building forecasting, recommendation, pricing, and AI-driven decision systems that operate across a huge global dataset, with models directly influencing commercial decisions at scale.
The role is heavily focused on machine learning engineering, particularly around time-series forecasting, scalable ML systems, feature stores, and MLOps. There’s also some exposure to generative AI and LLM-related work, but this is primarily a deeply technical ML engineering role rather than a pure GenAI position.
What makes the opportunity stand out is the blend of scale, technical complexity, and visibility. You’d be joining a relatively small but high-calibre AI team with strong research and engineering backgrounds, helping shape systems that directly influence pricing, marketing, and customer experience across thousands of businesses globally.
They’re looking for somebody who can stay hands-on technically while also helping guide more junior engineers and contribute to the wider technical direction of the team.
The environment feels like a startup within a larger global business. There’s plenty of ownership, freedom to influence technical decisions, and the opportunity to work on genuinely impactful AI systems at scale.
The setup is hybrid with two days per week onsite in London.
Experience around forecasting, time-series modelling, recommendation systems, production ML infrastructure, or large-scale MLOps environments would all be highly relevant.
Salary: £100,000 - £120,000 plus equity and benefits.
APPLY NOW for immediate consideration.
London Hybrid | £100,000 – £120,000 + Equity
This is a genuinely interesting opportunity for someone who enjoys solving large-scale, real-world machine learning problems rather than purely experimental work.
The team is building forecasting, recommendation, pricing, and AI-driven decision systems that operate across a huge global dataset, with models directly influencing commercial decisions at scale.
The role is heavily focused on machine learning engineering, particularly around time-series forecasting, scalable ML systems, feature stores, and MLOps. There’s also some exposure to generative AI and LLM-related work, but this is primarily a deeply technical ML engineering role rather than a pure GenAI position.
What makes the opportunity stand out is the blend of scale, technical complexity, and visibility. You’d be joining a relatively small but high-calibre AI team with strong research and engineering backgrounds, helping shape systems that directly influence pricing, marketing, and customer experience across thousands of businesses globally.
They’re looking for somebody who can stay hands-on technically while also helping guide more junior engineers and contribute to the wider technical direction of the team.
The environment feels like a startup within a larger global business. There’s plenty of ownership, freedom to influence technical decisions, and the opportunity to work on genuinely impactful AI systems at scale.
The setup is hybrid with two days per week onsite in London.
Experience around forecasting, time-series modelling, recommendation systems, production ML infrastructure, or large-scale MLOps environments would all be highly relevant.
Salary: £100,000 - £120,000 plus equity and benefits.
APPLY NOW for immediate consideration.
