At Stint, our machine learning engineers sit at the centre of how intelligence reaches the real world. You’ll work shoulder-to-shoulder with data scientists, researchers, and engineers to build models, architect data systems, and power decisions across thousands of hospitality sites. One day you might be building a demand forecasting model; the next you’re shaping data pipelines, deploying models into production, or tuning performance in a high-traffic environment. Your work will drive real-time decisions inside mobile apps, operational systems, and the tooling used by some of the UK’s biggest hospitality brands. You’ll help turn complex, messy, multi-source data into the intelligence behind our platform, and play a key role in scaling our AI systems as we expand across the UK and internationally. We are an office-first, collaborative team and this role is based in Camden 3-4 days a week What you will be doing: Building and maintaining scalable machine learning models to support data integration into our customer-facing mobile and web-apps as well as internal dashboards Designing and implementing data architecture to optimize data storage, retrieval, and processing Developing AI models to understand, predict and deploy labour in accordance to demand and to monitor and improve quality of service in hospitality Developing ETL processes to ingest, transform, and load data from various sources, specifically APIs Collaborating with data scientists, data engineers and software engineers to understand data needs for our customer-facing mobile and web-apps Working with internal stakeholders (e.g., Head of Ops, Head of Commercial) to understand and shape data requirements for internal data-driven decision making Creating and maintaining data documentation, monitoring pipeline performance, and troubleshooting issues This position might suit you, if you have: Strong foundations in mathematics, statistics, and modelling, with a keen ability to interpret data patterns and derive relevant insights Proven hands-on experience in developing production-grade machine learning products, preferably in one or more of the following areas: demand prediction, computer vision or optimisations Strong experience with ML Ops, data architecture, data engineering best practices, and scalable data solutions Proficiency in data modeling techniques, database design, and data normalization Solid experience with Python and SQL, ideally with experience using data processing frameworks (e.g. Airflow, Pytorch, Spark) Understanding of machine learning techniques, including supervised and unsupervised learning, with the ability to select and apply the right models to business problems Familiarity with the AWS cloud platform, particularly with AI/ML services such as SageMaker, Lambda, and related data processing tools Willing to develop basic to intermediate proficiency in backend development (Python with Django, Go) to support deployment and integration of ML models into the product ecosystem Familiarity with data versioning and data quality management practices Familiarity with build and deployment automation and CI/CD Ideally: Experience with data lakes, warehousing, and other data storage patterns Proficiency with cloud platforms such as AWS or Azure, with experience using data services such as Apache Airflow, terraform or SageMaker What we can offer you: Private medical insurance A social, friendly and welcoming team based in the heart of Camden Office gym membership Ownership shares in a well-funded, growing start-up Dog friendly office! Free office fruit and snacks Office dinner if working late Regular office breakfasts and lunches