Machine Learning Engineer | Generative AI | AWS | End-to-End ML SolutionsLocation: London-based | HybridPlease note: Sponsorship is not offered for this positionWe’re working with a leading organisation on a mission to become one of the most insight-driven businesses in its sector, placing machine learning and generative AI at the core of customer experiences, operational optimisation, and strategic decision-making.This is a fantastic opportunity for a skilled Machine Learning Engineer to build and deploy scalable, production-level ML solutions, working closely with Data Scientists and cross-functional teams to drive measurable business impact.You’ll play a pivotal role in integrating machine learning models into end-to-end pipelines, supporting strategic initiatives such as customer engagement, automated insights, and decision-support tooling. You’ll also contribute to shaping the frameworks, infrastructure, and shared tooling that enable safe, responsible, and efficient AI experimentation and deployment.If you’re passionate about problem-solving, applying ML to real-world challenges, and bringing ideas to life in production environments, this role is a great fit.What You’ll Be DoingMachine Learning EngineeringBuild, deploy, and maintain ML models as services, streaming applications, or batch jobs across real-time and offline platforms.Develop scalable model APIs with strong CI/CD and observability practices.Implement model testing, monitoring, and rollback capabilities in production environments.Collaborate with Data Scientists to translate prototypes into reliable, maintainable ML applications.Identify opportunities to develop new ML solutions in partnership with Data Science teams.Platform & ToolingAutomate and standardise ML infrastructure using Docker, Kubernetes, and Terraform.Support and develop monitoring dashboards for key ML and AI services.Ensure cloud-native, secure, and cost-efficient deployments in AWS environments.Contribute to the development of shared platforms and tooling that enable model deployment and experimentation.ComplianceAdhere to governance, risk, and compliance obligations relevant to the role.Identify and escalate non-compliance issues when necessary.Proactively challenge processes that may impact compliance standards.Complete all mandatory compliance training and engage with compliance teams for clarification when needed.What You’ll Bring3–5 years of experience in machine learning engineering and data science.Advanced degree (PhD or Master’s) in a numerate discipline.Excellent programming skills in Java and Python for production systems.Strong foundations in machine learning and data science.Experience deploying ML models as APIs, batch jobs, or streaming services (e.g., Kafka Streams).Proficiency in containerised application deployment with Kubernetes.Demonstrated experience building ML solutions from concept to delivery.Strong cloud engineering skills (AWS preferred; Terraform or CloudFormation a plus).Excellent communication and collaboration skills.Up-to-date knowledge of modern ML and AI developments.Why JoinThis is a chance to work on impactful machine learning use cases that shape the future of customer experiences and business operations. You’ll be part of a collaborative environment where innovation is encouraged, and you’ll have the autonomy to influence tooling, frameworks, and production ML strategy.Please note: Sponsorship is not offered for this position. Candidates must have the existing right to work in the relevant location.