
digiLab helps governments and organizations make confident decisions on complex, safety-critical engineering problems when data is sparse or uncertain. It provides the Uncertainty Engine, a…

digiLab helps governments and organizations make confident decisions on complex, safety-critical engineering problems when data is sparse or uncertain. It provides the Uncertainty Engine, a…
Core product: The Uncertainty Engine — an explainable, uncertainty-aware decision intelligence platform
Founded: 2021
Headquarters: Exeter, United Kingdom
Customers / sectors: Safety-critical and highly regulated sectors (energy, healthcare, public sector)
Uncertainty quantification and explainable AI for safety-critical, highly regulated decision-making (e.g., fusion energy, water, shipping, healthcare, public sector).
2021
Software Development
99200
UK Research & Innovation grant (~£99.2k) listed Aug 2024
Founded/spinout from the University of Exeter
3922000
Last funding date reported
“East X Ventures, Oxford Technology Management, UK Innovation & Science Seed Fund”
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In a world of immense uncertainty, digiLab is a pioneering AI company that empowers governments and organisations in safety-critical or highly regulated industries to solve critical, complex, and high-stakes challenges using machine learning and uncertainty quantification.
From forging a path to clean energy to life-saving medical diagnostics and beyond, making critical decisions with unwavering confidence is difficult, especially when data is complex, sparse, or incomplete. This is where digiLab's expertise shines through.
Our trustworthy and explainable AI platform, The Uncertainty Engine, supported by our team of machine learning specialists and data scientists, enables decision-makers to accelerate innovation, reduce the risk of failure, turn insight into action, and deliver greater value through more informed and confident decisions.
Summary The Senior Machine Learning Engineer (Platform) is a full-time position (Monday to Thursday), reporting directly to the Lead Software Engineer. This role is central to the ongoing development and maintenance of digiLab's core product, The Uncertainty Engine. It sits at the intersection of probabilistic machine learning, uncertainty quantification, and large-scale scientific software , with a strong focus on Python development within a fast-paced, collaborative, and dynamic engineering environment.
The Role As a Senior Machine Learning Engineer (Platform) at digiLab, you will be responsible for:
Duties may evolve, and you may be asked to take on other reasonable responsibilities within your competence to support our growth. Required Skills & Experience
In Addition, Some ‘nice To Haves' Are
Location: On site.
As an ambitious, rapidly-growing start-up, we're looking for proactive, adaptable people who thrive in a fast-paced environment. Our standard working hours are 9.00–5.30pm, Monday to Thursday, though some flexibility outside these hours may be required to meet business needs. Our Culture and Values At digiLab, we prioritise work-life balance with a 4-day workweek (Monday to Thursday), offering a full-time salary and three-day weekends every week! Our team is built on strong connections, with regular socials like game nights, bouldering, and paddleboarding.
We foster a culture of innovation, trust, and collaboration. Our values include:
Benefits We value enthusiasm and loyalty, and we're committed to offering a great work-life balance. Along with the exciting challenges this role provides, we offer a range of benefits including:
Equal Opportunities digiLab is an equal opportunity employer. We welcome applications from candidates of all backgrounds and are committed to ensuring our recruitment processes are fair, inclusive, and legally compliant. We take equality, dignity, and non-discrimination seriously.
Final Note We aim to respond to every applicant, but due to high application volumes, we may not be able to respond individually. Thank you for your interest in joining the digiLab team. The information you provide will be stored and used in line with our Privacy Notice.
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