Machine Learning Engineer - 3-4 Days per week in Camden office

We’re partnering with a fast-growing, well-funded tech company transforming how hospitality businesses staff, plan, and operate in real time — and they’re looking for a Machine Learning Engineer to join their team.

This is a hands-on, high-impact role where you’ll take models from idea → production → real-world impact across thousands of sites. You’ll be working on everything from demand forecasting to data pipelines and production deployment in a high-traffic environment used by major UK brands.

This isn't your typical Machine Learning role focussed on LLMs. They are looking for talented engineers with a quantitative background and experience with statistical models.

What you’ll be doing:

• Building and deploying scalable ML models powering mobile apps and internal tools

• Designing data architecture for efficient storage, processing, and retrieval

• Developing forecasting and optimisation models for staffing and operations

• Owning ETL pipelines integrating multi-source data (APIs, internal systems)

• Collaborating with data scientists, engineers, and business stakeholders

• Monitoring, maintaining, and improving production ML systems

What they’re looking for:

• Strong foundations in maths, statistics, and modelling

• Experience building production-grade ML systems (e.g. forecasting, optimisation, CV)

• Solid ML Ops and data engineering experience

• Proficiency in Python & SQL (Airflow, PyTorch, Spark a plus)

• Experience with AWS (SageMaker, Lambda, etc.)

• Interest in backend development (Django or Go)

• High level STEM Degree from a leading university.

Nice to have:

• Experience with data lakes / warehousing

• Familiarity with CI/CD, data versioning, and data quality practices

What’s on offer:

• Private medical insurance

• Equity in a high-growth startup

• Gym membership

• Dog-friendly office

• Regular team meals, snacks, and a collaborative, social culture

If you’re excited by real-world ML applications, enjoy building end-to-end systems, and want to make a tangible impact — we’d love to hear from you.

Apply now or message me directly for more details.