Machine Learning Engineer in London

We are looking for a Machine Learning Engineer to develop and implement novel machine learning approaches for weather forecasting, extreme-event prediction and energy applications.

You will work with large, high-dimensional and spatiotemporal datasets, including weather forecasts, reanalysis data, satellite imagery and real-time time-series data.

The role spans the full machine learning workflow, from data engineering and model development to rigorous validation, deployment and improvement using evidence from real-world operation.

As an early technical hire, you will work closely with the founders and wider Qronon team, taking significant ownership of machine learning development.

You will run numerical experiments, implement promising methods from the latest research, and help turn new forecasting approaches into reliable systems for real-world weather and energy applications.

What You'll Work On

• Develop and improve quantum-enhanced machine learning models for weather forecasting and extreme-event prediction.
• Run experiments with Qronon models for specific clients and projects.
• Keep up to date with relevant machine learning research and implement promising methods in the Qronon codebase.
• Deploy models in live environments and improve them using evidence from real-world operation.
• Help architect high-volume data pipelines and collect data alongside the data team.
• Help solve forecasting and optimisation problems across energy and other weather-sensitive sectors.

About You

A Ph D, or a Master's degree with relevant experience, in machine learning, applied mathematics, statistics, atmospheric science, physics, computer science, engineering or a related field.

We value strong research ability, technical depth and a track record of excellent work.

• Strong foundations in machine learning, including modern deep-learning architectures and training methods.
• Strong Python and Git experience, with experience using JAX, Py Torch or similar modern ML frameworks.
• Experience working with large, high-dimensional, time-series or spatiotemporal datasets.
• Understanding of statistical validation and, uncertainty.
• Ability to take ideas into code implementation.
• Clear written and verbal communication and an ability to work across research, engineering and product.
• Motivation to work on technically challenging problems with real-world impact.
• Machine learning for weather, climate, Earth observation or another physical dynamical system.
• Experience with architectures for spatiotemporal prediction, such as graph neural networks, transformers, neural operators, state-space models or generative methods.
• Probabilistic forecasting, ensemble methods, calibration, data assimilation or extreme-event evaluation.
• Experience with atmospheric or geospatial datasets and tools such as ERA5, Net CDF, Zarr, xarray or Dask.
• Distributed training, GPU optimisation or HPC environments such as Slurm.
• Quantum computing, quantum machine learning or quantum-inspired methods. Relevant to Qronon's longer-term research direction, but not required for success in the role.
• Numerical weather prediction, atmospheric dynamics or operational forecast verification.
• Taking research models into live products, APIs, commercial pilots or other operational settings.
• Publishing high-quality research, contributing to strong open-source projects, or communicating technical work publicly.

About Us

Qronon develops predictive models for complex physical systems by combining quantum computing methods with classical machine learning.

Starting with weather forecasting, its research focuses on nonlinear dynamics, uncertainty and computational efficiency, with longer-term applications across climate risk, energy and other physical systems.

Qronon is backed by research funding from the UK's Advanced Research + Invention Agency (ARIA) and leading global investors.

We are expanding our technical team and you will join at an early stage, working closely with the founders and taking significant ownership over Qronon's machine learning development.

You will have the opportunity to shape both the technology and how the team grows as we move from frontier research to real-world deployment.

• £40,000 - £70,000, based on experience.
• Flexible hours.
• 30 days of annual leave, excluding UK public holidays.