Senior Machine Learning Engineer

Senior Machine Learning Engineer | AI for Scientific Discovery

Climate Tech Start-Up

London, 5 days a week in offic

£100,000 - £130,000 + meaningful equity

Your next model could help discover the materials powering the energy transition.

We’re partnering with a mission-driven, deep-tech start-up applying advanced ML to commercially significant scientific challenges.

Following a recent substantial funding raise, they’re looking for a mathematically strong engineer or applied researcher to take ownership of core modelling work, from developing ideas through to implementation and rigorous evaluation.

The work involves complex scientific data, limited labelled examples and predictions where understanding uncertainty matters. You’ll have substantial influence over the technical approach, working closely with the founding team.

What you’ll do

• Develop and implement deep learning methods for challenging datasets.
• Explore approaches across representation learning, limited supervision and physics-informed modelling.
• Design robust experiments and assess how models perform on unfamiliar data.
• Help shape the modelling roadmap and communicate findings across the business.

What you’ll bring

• A PhD or equivalent depth in ML, statistics, applied mathematics, physics or a related quantitative field.
• Strong hands-on deep learning experience, including PyTorch.
• Evidence of developing or meaningfully adapting methods.
• Rigorous experimental judgement and clear communication.

Your background could be in applied research, computer vision, scientific ML, imaging or another field involving complex real-world data. Previous experience in the company’s industry is not essential.

The opportunity

A core technical role offering autonomy, close collaboration with the founders and a direct connection between your research and commercial decisions.

Given the early life stage of the business, joining at this stage offer compressed learning in a rapid-growth, high performance environment.

This suits ambitious, innovative, resilient folk, people who are drawn to solving abstract problems, with a commercial mindset.