Machine Learning Engineer

Searchworks is partnering with a high‑growth hospitality technology scale‑up that is building the “staffing brain” for venues across the UK. Their AI‑powered platform helps operators stay perfectly staffed as demand changes by the hour, using multi‑year data, forecasting models and an on‑demand workforce across thousands of sites.

We’re now looking for a Machine Learning Engineer to sit at the heart of their data and AI function. You’ll work closely with data scientists, engineers and product teams to turn messy, multi‑source data into robust models and data systems that drive decisions inside mobile apps, internal tools and operational systems.

The role

• Build and maintain scalable machine learning models that power customer‑facing mobile and web apps as well as internal dashboards.
• Design and implement data architecture to optimise how data is stored, processed and accessed.
• Develop AI models to forecast demand, deploy labour in line with that demand, and monitor/improve service quality in hospitality venues.
• Build ETL processes to ingest, transform and load data from multiple sources, especially third‑party APIs.
• Collaborate daily with data scientists, data engineers and software engineers to understand data needs across products.
• Work with internal stakeholders (e.g. Head of Ops, Head of Commercial) to shape data requirements for internal decision‑making.
• Own data documentation, monitor pipeline performance and troubleshoot production issues.

Your background

• Strong foundations in mathematics, statistics and modelling, with the ability to interpret data patterns and turn them into practical insight.
• Proven experience building production‑grade ML products, ideally in demand prediction, computer vision or optimisation.
• Solid experience across ML Ops, data architecture and data engineering best practices and scalable data solutions.
• Proficiency in Python and SQL, ideally with frameworks such as Airflow, PyTorch or Spark.
• Good understanding of supervised and unsupervised learning and how to choose/apply the right model to a business problem.
• Familiarity with AWS (e.g. SageMaker, Lambda and related data tools).
• Willing to develop basic–intermediate backend skills (Python with Django, Go) to support model deployment and integration.
• Familiar with data versioning, data quality management and CI/CD / deployment automation.

Competitive salary plus equity in a well‑funded, growing start‑up. Private medical insurance and office gym membership. Office‑first culture (Camden) with 3–4 days per week on‑site, in a social, friendly and welcoming team. Dog‑friendly office, free snacks, regular breakfasts/lunches and dinner if you’re working late.