Machine Learning Engineer

Machine Learning Engineer (Production ML / MLOps)Location: London (Hybrid/Other locations available)Salary: Up to £100k + BenefitsThe OpportunityA leading global professional services organisation is expanding its advanced analytics and AI capabilities and is seeking a Machine Learning Engineer with strong production and MLOps experience to join its growing technology and data team.Operating across multiple sectors including financial services, public sector, healthcare, and technology, the organisation helps clients solve complex business challenges through data-driven insights, automation, and advanced AI solutions. With significant investment being made in its digital and AI transformation initiatives, the firm is building a team of engineers and data specialists responsible for delivering scalable machine learning systems that support real-world client applications.This role will sit within a collaborative team of data scientists, engineers, and technology consultants, working on the design and deployment of machine learning models that move beyond experimentation and into production environments.Key ResponsibilitiesDesign, build, and deploy machine learning models into production environmentsDevelop scalable ML pipelines and automated training workflowsCollaborate with cross-functional teams including data scientists, software engineers, and business stakeholdersImplement CI/CD processes for machine learning systemsMonitor model performance, manage model drift, and optimise inference pipelinesBuild APIs and services to integrate machine learning capabilities into enterprise applicationsContribute to the development and evolution of the organisation’s ML platform and infrastructureRequired Skills & ExperienceStrong programming skills in PythonExperience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learnDemonstrable experience deploying machine learning models into production systemsExperience with Docker and Kubernetes for containerisation and orchestrationFamiliarity with MLOps tools such as MLflow, Kubeflow, Airflow, or similarExperience working with cloud platforms such as AWS, GCP, or AzureStrong understanding of data pipelines and large-scale data processingDesirable ExperienceExperience with distributed data processing (e.g. Spark or Databricks)Knowledge of model monitoring and observability toolsExperience building real-time inference systems or APIsExposure to modern Generative AI or LLM frameworksWhat’s on OfferOpportunity to work with a global professional services organisation delivering AI solutions to major clientsExposure to a wide range of industries and complex data challengesA collaborative, innovation-focused engineering environmentCompetitive salary and benefits packageFlexible working arrangements (remote/hybrid)Strong opportunities for career development within a growing AI practice