Extract, clean, and structure data from internal systems
Design and develop end-to-end ML pipelines (data ingestion → model → deployment)
Train, evaluate, and optimise models to improve accuracy and business impact
Integrate machine learning models into internal tools and existing systems
Work with stakeholders to translate business problems into ML solutions
Continuously monitor and improve model performance
Introduce and promote ML best practices, standards, and tooling
Contribute to building and scaling the organisation’s AI capability
Collaborate with engineering teams to ensure scalable and reliable deployment of solutions

4+ years total experience (Mid–Senior level)
Python – 3+ years (substitutes: other ML-focused languages for exceptional candidates)
Machine Learning – 3+ years
SQL / Databases – 3+ years (substitutes: other database technologies)
.NET / C# – 1+ year
Azure – 1+ year (substitutes: AWS)
Experience building production-grade ML systems and pipelines
Ability to work with large datasets (structured and unstructured)
Strong problem-solving skills with a focus on real-world business impact
Experience working closely with stakeholders and cross-functional teams
Project ownership experience

Machine Learning Engineer – Mid/Senior

Key skills