Software Engineer Platform

## About the company GTL is a well-funded, early-stage startup developing state-of-the-art digital technologies to better understand, diagnose and treat blood cancer patients. We have built an exceptional, small-by-design, interdisciplinary team to translate leading academic research into real impact on global health. Since 2023 we have made considerable progress in developing our technology, deploying our first generation of algorithms commercially with global biopharma, and working with world-leading academic medical centres to continue developing and validating new biomarker tools that improve patient outcomes. As a member of our small team, you will have the opportunity to help shape our journey and build on our principles of collaboration, focus, and invention. ## About the role We are looking for a Software Engineer - Platform to play a critical role in the development of the core data and software platform underpinning our AI-enabled biomarker products. This is a highly creative, fast-paced environment. Our team is deeply interdisciplinary, and you will work closely with, leadership, machine learning scientists, software engineers and clinical scientists to build the systems that allow us to ingest, organise, serve and interact with complex clinical and imaging data. This is a high-ownership role in a small company. You will help shape how data flows through the organisation, from hospital and biopharma collaborators into internal research and product workflows. The successful candidate will be excited by ambiguous problems, comfortable building from scratch, and motivated by creating robust, usable systems that accelerate scientific and product development. ## What you'll do - Contribute production development across the core application stack, including backend services, APIs, data workflows and user-facing internal tools. - Design and build systems to ingest, organise and serve complex, multi-modal datasets, including high-resolution whole slide images, tabular clinical data and unstructured reports. - Develop robust ETL and processing pipelines to support onboarding of new collaborator datasets quickly and reliably. - Build thoughtful internal tools and interfaces that enable machine learning scientists and other technical users to access clean, well-structured data fast. - Contribute to schema and application design for evolving data models, where new data sources and formats must be integrated over time. - Collaborate closely with machine learning scientists and engineers to support model development, deployment and evaluation workflows. - Make critical architectural decisions across application, database and infrastructure layers, balancing speed, flexibility, reliability and scale. - Help develop and operate our cloud-based platform and data infrastructure, with a practical, cloud-agnostic mindset. - Work in a hands-on way across the stack, debugging issues, improving developer workflows and shipping pragmatic solutions in a small-team environment. ## What you bring ### Essential - Strong software engineering experience across backend and frontend systems, with the ability to build and ship end-to-end products and internal tools. - Experience designing and building APIs, application services and data-intensive systems in production. - Hands-on experience working with databases and data pipelines, including designing schemas and handling messy real-world data. - Experience building systems that work across multiple data modalities, or with complex and evolving datasets. - Comfortable working in cloud environments and deploying production infrastructure or services on at least one major cloud provider. - Ability to work independently, take ownership and make progress in ambiguous, fast-moving environments. - A practical, builder mentality: you are comfortable getting stuck in, solving problems from first principles, and wearing multiple hats when needed. - UK-based or willing to relocate to the UK, with the ability to travel to London regularly. ### Nice to have - Experience working with high-resolution image data, medical data, scientific data, or other large and complex datasets. - Experience building OCR, document extraction or other pipelines for unstructured records and reports. - Experience across both relational and non-relational databases. - Experience with infrastructure-as-code, CI/CD and cloud-native data services. - Experience working in an early-stage startup or similarly high-ownership environment. - Familiarity or an interest in healthcare, biotech, digital pathology, or machine learning-enabled products. - Experience with our chosen flavour tech-stack (Python, MySQL, GCP, Azure) ## Opportunity This is an opportunity to join a small, high-calibre team and take ownership of foundational engineering work at a pivotal stage of company growth. You will work alongside talented machine learning scientists and engineers to build the platform that supports our research, partner delivery, and future products. The role is especially well suited to someone who enjoys building from the ground up, moving quickly, and having tangible impact across an organisation and field. ## Working environment We primarily work remotely with a strong emphasis on efficient processes that enable high-quality work across asynchronous teams. At the same time, we recognise the importance of spending time together in person to share knowledge, solve hard problems, and build strong working relationships. We therefore expect this role to involve regular travel to London and Oxford. Indicatively, a typical month may involve 2-8 in-person days. As a team, we value: - Concise and engaged communication - we communicate clearly to work effectively in a remote setting. - Pride in high-quality work - we pay attention to detail and deliver to the highest standard. - A strategic approach - we think critically and creatively about complex issues. We identify the underlying patterns and leverage them to develop effective strategies - Collaborative co-creation - we are open t