Senior Software Engineer (Machine Learning)

digiLab is a formative AI company with world-leading specialists in uncertainty quantification, applied where the stakes are highest and the margin for error is smallest. Our customers are among the largest and most advanced engineering and science-led organisations in the world, and they're using our technology to tackle some of society's biggest challenges. How do we make fusion energy a commercial reality? Can we drive down the cost of renewable energy and accelerate the transition to a sustainable future? How do we support coral reef restoration, or strengthen Britain's national security? These are just a few of the critical questions our technology is helping to answer. At the heart of our work is the Uncertainty Engine, digiLab's trustworthy and explainable AI platform, enabling our customers to accelerate innovation, reduce risk, and deliver real value through more confident decisions. We are looking for ambitious team members to help shape our pioneering technology and tackle some of the world's most impactful problems. Summary: The Senior Software Engineer 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 encompasses a broad range of responsibilities that leverage expertise in software engineering and machine learning, with a strong focus on Python development within a fast-paced, collaborative, and dynamic engineering environment. The role: As a Senior Software Engineer at digiLab, responsibilities include: • Collaborate with a cross-functional team to help lead the design, development, and maintenance of high-quality software solutions • Consume and extend our internal machine learning library to surface ML functionality to users through the backend • Design and build the scalable, high-performance backend services and APIs that deliver functionality to users, applying security best practices throughout • Implement software design patterns, SOLID principles, and architectural best practices • Own CI/CD pipelines and deployments, keeping production systems reliable and performant • Provide technical support and lead incident investigations • Champion Scrum and contribute to team process improvements • Collaborate with product management to translate business requirements into technical solutions • Foster a collaborative, learning-oriented environment within the team • Adopt AI tools to assist and accelerate your work Duties may evolve, and you may be asked to take on other reasonable responsibilities within your competence to support our growth. Required Skills & Experience: • Significant industry experience in (scientific) software development • Proven experience building production APIs with FastAPI (or similar async Python frameworks) • Strong working knowledge of modern machine learning — able to understand, integrate, and extend the functionality of an ML library (NumPy, SciPy, Pandas, and frameworks such as scikit-learn or PyTorch) • Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough to design robust interfaces around them • Experience with DevOps and MLOps • Degree-level qualification in computer science or related field • Deep understanding of Python • Familiarity with Linux, bash, and the command line • Ability to write logical, consistent, self-explanatory code • Understanding of software design patterns, SOLID and DRY principles, and architectural patterns • Experience with Git/GitHub and best practices • Knowledge of the software testing pyramid and types of automated testing (smoke, component, unit, performance, load, end-to-end) • Experience with Docker and other cont