Machine Learning Engineer

Looking for a ML engineer with graph-based modelling experienced to join a venture-backed, Cambridge University spin-out transforming how the world discovers critical minerals.

About us

The biggest risk to all human progress is securing a sufficient, diversified supply of critical minerals. To meet energy transition and data centre demands, over the next 25 years we will need to mine the same amount of copper as we have ever mined in all of human history. Today’s methods for discovering and developing mines simply can’t scale to this challenge.

We're a Cambridge University spin-out using explainable AI to transform the way that critical mineral mines are found and developed. Our uncertainty-aware models map subsurface resources from multimodal data, helping mining companies make faster and more accurate drilling decisions. This can halve drilling costs, double exploration areas, and bring critical mineral projects online sooner.

We have just closed an over-subscribed funding round, and are expanding the team to turn our innovation into a product and scale deployment.

The role

We are looking for a full-time Data Scientist/Machine Learning Engineer with experience in graph-based ML models to lead data pipeline and model development. You will:

·      Build & automate data processing pipelines.

·      Implement & optimise graph-based ML models.

·      Create visualisations for geospatial data.

·      Explore and develop new product features.

As a small, agile team there will be lots of opportunities to contribute to and take ownership of many different aspects across the business.

What we’re looking for

Core competencies:

·     Strong experience coding in Python (inc. PyTorch & PyTorch Geometric) on collaborative version-controlled projects.

·      Ability to take initiative, work independently and communicate clearly in a multidisciplinary team.

·      Background in graph-based modelling or extensive ML implementation experience.

·      Experience working with geospatial datasets.

Extras:

·     Background in geophysics - preferably with experience in mining.

·     Experience setting up and maintaining cloud infrastructure.

·     GIS & 3D visualisation skills.

The Details

·     £70-100k pa plus meaningful equity, dependent on seniority

·     Working in person from London

Why Join Us?

We’re a small, ambitious team moving fast – and you’ll be a core part of shaping the future of our product and technology. Expect a flat structure with hands-on responsibility, rapid learning, and the chance to work on problems with real-world impact.