Senior Machine Learning Specialist

Senior ML Ops Engineer York | Hybrid Salary: Up to £75,000 Company Overview Join a leading international organisation with an ambitious technology and data strategy. The organisation combines a strong commercial focus with a collaborative, inclusive culture and invests in modern cloud, data and machine learning capabilities. You'll join a growing technology function where innovation, ownership and continuous improvement are encouraged. The Role We're looking for an experienced Machine Learning Engineer to help build and scale production-grade machine learning solutions. You'll develop the infrastructure, APIs and deployment pipelines that support the full ML lifecycle, working closely with Data Scientists, Data Engineers and Platform Engineers. This is a hands-on role with the opportunity to shape MLOps practices and the organisation's growing machine learning capability. Key Responsibilities

• Build and maintain infrastructure for real-time and batch ML model deployment.
• Develop Python APIs using Flask, FastAPI or similar frameworks.
• Design and maintain CI/CD pipelines for ML deployment.
• Automate the ML lifecycle, including data preparation, training, evaluation, deployment and monitoring.
• Develop and maintain model registries and monitoring solutions.
• Build reliable, scalable cloud-based ML services.
• Write high-quality, tested and maintainable Python code.
• Apply software engineering, TDD and Agile best practices.
• Collaborate with Data Scientists, Data Engineers and Platform Engineers.
• Monitor and improve the performance, reliability and security of ML services.
• Help mature the organisation's data science and MLOps capabilities. Qualifications & Skills Required
• Bachelor's/Master's degree in a quantitative discipline or equivalent experience.
• 3–5 years' experience in machine learning engineering or a related role.
• Strong Python development experience.
• Experience deploying and supporting ML models in production.
• Good understanding of machine learning and data science principles.
• Experience with APIs, preferably Flask or FastAPI.
• Strong software engineering and testing practices.
• Experience with TDD, Git and CI/CD.
• Experience with Terraform or similar Infrastructure as Code tools.
• Hands-on experience with Azure, AWS or GCP.
• Familiarity with Docker and containerised deployments.
• Understanding of monitoring, logging and API operations.
• Strong problem-solving and communication skills.
• Experience working in Agile teams. Preferred
• Experience in financial services, insurance or another regulated industry.
• Experience with MLOps platforms and tooling.
• Experience working across multiple cloud platforms.
• Experience taking data science models from development into production. Benefits
• Competitive salary and performance-related bonus.
• Employer pension contribution.
• Health and wellbeing benefits.
• Generous annual leave.
• Flexible/hybrid working.
• Professional development and training opportunities.
• Exposure to modern cloud, data and machine learning technologies.
• Collaborative environment with opportunities to influence and shape ML engineering practices. Equal Opportunity Statement