Machine Learning Engineer

Enso Recruitment is proud to be working with a fast-growing, data-driven SaaS organisation delivering predictive analytics and AI solutions to critical infrastructure sectors. Their platform uses advanced data science, machine learning, and cloud technologies to solve real-world operational and environmental challenges.

They are now seeking a Machine Learning Engineer to join their Data & Modelling team and play a key role in developing and deploying ML-driven features into a live production platform.

The Opportunity

This is a hands-on, delivery-focused role suited to a Machine Learning Engineer who enjoys taking ownership of problems from ideation through to deployment.

You’ll contribute to the design, development, and scaling of predictive models that operate on complex time-series, environmental, and sensor-based datasets. The role offers the opportunity to work on meaningful, real-world challenges where your models will directly influence product outcomes and customer impact.

Key Responsibilities

• Develop and deploy predictive ML models within a cloud-based SaaS platform


• Perform exploratory data analysis and visualisation on large-scale datasets


• Design scalable feature engineering and data transformation pipelines


• Work with time-series, geospatial, and environmental sensor data


• Lead the development of new ML-driven product features from proof-of-concept to production


• Collaborate closely with domain experts to shape modelling approaches


• Present insights and technical findings to both internal and external stakeholders


• Contribute to CI/CD workflows and continuous delivery practices


• Support testing, debugging, and optimisation of deployed models


• Continuously identify opportunities for improvement across modelling processes

About You

• 3+ years’ experience in Data Science, Machine Learning Engineering, or a related discipline


• Strong Python expertise (Pandas, Scikit-learn or similar ML frameworks)


• Experience with data exploration, analysis, and visualisation


• Experience building and deploying predictive models in production environments


• Strong understanding of feature engineering and data transformation


• Ability to conceptualise solutions and communicate clearly to stakeholders


• Collaborative mindset with the ability to operate in a fast-paced, growing environment


• Curious, proactive, and passionate about applying ML to real-world problems


• Share options


• Pension


• Enhanced parental leave


• On-site parking