Job Description

Machine Learning Engineer

Department: Data

Employment Type: Full Time

Location: London, UK

Reporting To: Jack Weeks

Compensation: £50,000 - £80,000 / year

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