Software Engineer Intern (6 months)

Job Title

Software Engineer Intern (6 months) – Starting Summer 2027

Project Title: Subsurface Monitoring for CO2 Storage & Geothermal

About SLB

We are a global technology company, driving energy innovation for a balanced planet.

At SLB we create amazing technology that unlocks access to energy for the benefit of all. That is our purpose. As innovators, that has been our mission for 100 years. We are facing the world’s greatest balancing act- how to simultaneously reduce emissions and meet the world’s growing energy demands. We’re working on that answer. Every day, a step closer.

Our collective future depends on decarbonizing the fossil fuel industry, while innovating a new energy landscape. It’s what drives us. Ensuring progress for people and the planet, on the journey to net zero and beyond. For a balanced planet.

Our purpose: Together, we create amazing technology that unlocks access to energy for the benefit of all. You can find out more about us on https://www.slb.com/who-we-are

Location

Abingdon, Oxfordshire

Description & Scope

​Join a team building cutting-edge software for monitoring CO2 storage and geothermal energy projects — work that sits right at the intersection of subsurface science, machine learning, and the energy transition.

You’ll help develop tools that let engineers see what’s happening deep underground, correlate it with surface data, and track how our monitoring solutions perform in the field.

Depending on your interests and background, you could work on:

• Surrogate model deployment & execution for subsurface monitoring — taking fast, data-driven models that track CO2 plume migration or thermal fronts (standing in for slow, expensive physics simulations) and running them end-to-end in production: model versioning, automated deployment through pipelines, model execution, and ongoing monitoring. Visualization for enhanced geothermal wells
• Designing intuitive components that turn complex subsurface parameters, correlated with surface measurements, into clear, actionable views for engineers. Reliability & performance monitoring
• Instrumenting the end-to-end solution to measure its accuracy, speed, and robustness, and helping make it production-ready.

What you’ll learn and take away

• Hands-on experience deploying and operating machine learning models (surrogate/reduced-order models) on real geoscientific and physics-based data, using modern MLOps pipelines.
• Experience combining subsurface and surface data to build a more complete picture of what’s happening in the reservoir.
• An understanding of how subsurface monitoring works in carbon storage and geothermal energy, and why it matters for the energy transition.
• Practical skills in scientific data visualization and communicating complex information to technical users.
• Exposure to what it takes to build reliable, well-monitored software testing, performance measurement, and MLOps-style thinking.
• The experience of working within a professional R&D team, from problem framing through to a demonstrable deliverable you can point to.​

Requirements:

• Studying a Bachelors or Masters in Computer Science or a related field
• ​Backend / MLOps — building services and automated deployment pipelines; model versioning and execution.
• Frontend — building data-visualization components and interactive views.
• Software Testing — automated testing, performance measurement, and reliability/monitoring.
• Machine Learning (desirable) — a working understanding of ML models is a plus​

SLB is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law.

The recruiting process and the position can be adapted to fit most disabilities, please do not hesitate to mention this when applying.