Carlos Les, PhD MIET
FOUNDING PARTNER
“Building a sophisticated deep learning model without the domain understanding is like serving a Michelin-starred dish without seasoning—we’re different, we bridge technical prowess with industry insight.”

Expertise: digital transformation, technical leadership, data-driven software solutions
Dr Carlos Les is an engineer with 9 years’ experience delivering innovation through software, data science, modelling and simulation and is a founding partner of OneEpsilon.
Highlights
Built from the ground up the data science capability for a digital engineering consultancy, driving strategic innovation and securing over 90% client retention across food, mining, aerospace and biomedical sectors.
Member of the Institution of Engineering and Technology (MIET) and skilled in modern software development, high-performance computing, optimisation, validation and verification.
Track record of successfully commercializing academic and industrial research, both numerical and experimental, into bespoke solutions.
Experience
Carlos holds Doctorate and master’s degrees in aerospace engineering and thermal sciences from Loughborough University and the University of Cambridge.
He began his career as a researcher at the National Centre for Combustion and Aerothermal Technology (NCCAT), where he developed pioneering techniques combining 3D temperature measurements with computer vision and finite-element methods. His innovative work helped validate Rolls-Royce's conjugate heat transfer models, contributing to significant cost savings in engine testing procedures. Carlos later joined Rolls-Royce's aerothermal research team, where he established new best practices for predicting combustion performance from limited data of thermoacoustic instabilities, advancing the development of low-emission aircraft engines.
In 2020, Carlos began his journey into consultancy, where he leveraged his technical background to become a versatile data science and software engineering professional. There, he built and led a data science team. His technical portfolio includes creating a full-stack knowledge base platform for medical device testing, developing physics-constrained machine learning models for food science, and probabilistic digital twins for mining fleet operations.
Throughout his career, Carlos has demonstrated expertise in software development, scientific computing, machine learning, and transforming cutting-edge research into commercially viable technological solutions across diverse industrial sectors.
Qualifications
MIET, Member of the Institution of Engineering and Technology.
PhD in Aerothermodynamics, Loughborough University.
MRes in Gas Turbine Aerodynamics, University of Cambridge.
MEng in Aeronautical Engineering, Loughborough University.