Machine Learning Engineer

Reference: ITA006327-Caity-1

Are you a Machine Learning Engineer who enjoys turning models and prototypes into real-world solutions that drive measurable business impact? This is an exciting opportunity to work at the intersection of machine learning, AI, software engineering, and data science, delivering production-ready solutions within a fast-paced, data-rich environment. Duties & Responsibilities

A leading digital business is seeking a Machine Learning Engineer to join its Decision Science team. This hands-on role focuses on transforming machine learning models, analytics assets, and AI solutions into reliable, scalable production systems. Working closely with data scientists, software engineers, product teams, and business stakeholders, you will bridge the gap between experimentation and deployment. You will be responsible for building, deploying, monitoring, and optimising machine learning solutions that improve decision-making, automate operational processes, and enhance customer outcomes. This role is ideal for a technically strong professional who combines software engineering discipline with practical machine learning expertise and a passion for delivering business value.

Key Responsibilities

• Develop, deploy, and maintain machine learning and AI-powered solutions in production environments.

• Design and enhance document intelligence and information extraction systems.

• Build solutions for classification, forecasting, optimisation, automation, and pattern recognition.

• Transform prototypes and analytical models into scalable, production-ready applications and services.

• Develop APIs, pipelines, and reusable machine learning services.

• Implement CI/CD processes, automated testing, containerisation, and model deployment practices.

• Integrate machine learning solutions into customer journeys and operational systems.

• Monitor model performance, data quality, prediction drift, and operational health.

• Investigate production issues and implement improvements to optimise reliability and performance.

• Define success metrics, conduct testing, and evaluate business impact.

• Contribute to technical documentation, design reviews, and knowledge sharing initiatives.

Job Experience and Skills Required

• Degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.

• Equivalent practical experience will also be considered.

• Strong professional Python development experience.

• Experience building and deploying production machine learning solutions.

• Experience moving models from experimental environments into operational workflows.

• Strong SQL and data engineering experience.

• Experience working with large and complex datasets.

• Exposure to automated testing, version control, and software delivery best practices.

• Experience supporting and troubleshooting production systems.

• Python and machine learning frameworks.

• SQL and database technologies.

• REST API development and integration.

• Machine learning model deployment and management.

• Data pipelines and event-driven architectures.

• Git and version control.

• Automated testing and CI/CD practices.

• Containerisation and cloud-based deployments.

• Monitoring, alerting, and model-performance tracking.

• Machine learning model evaluation and optimisation.

• Experience within financial services, lending, credit risk, collections, or fraud environments.

• MLOps tooling and experiment tracking platforms.

• Snowflake, Snowpark, dbt, or similar modern data platforms.

• OCR, document processing, and information extraction technologies.

• Real-time decisioning or scoring platforms.

• Model explainability and champion-challenger testing.

• Streamlit or similar lightweight application frameworks.

• Strong analytical and problem-solving abilities.

• Excellent software engineering discipline.

• Ability to communicate technical concepts to both technical and non-technical stakeholders.

• Strong attention to quality, maintainability, and reliability.

• Commercial mindset focused on delivering measurable outcomes.

• Ownership mindset from design through deployment and optimisation.

• Curiosity and passion for emerging AI, machine learning, and MLOps technologies.

Apply Now!

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If you have not received feedback within two weeks, please consider your application unsuccessful. Your profile will remain in our database for future opportunities.

For more information, contact: Caitlin Ferley Recruitment Consultant Linkedin:  www.linkedin.com/in/caitlin-ferley-b94a80218