Machine Learning Engineer

Location: London (Hybrid/Other locations available)

Salary: Up to £100k + Benefits

A 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.

• Design, build, and deploy machine learning models into production environments
• Develop scalable ML pipelines and automated training workflows
• Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders
• Implement CI/CD processes for machine learning systems
• Monitor model performance, manage model drift, and optimise inference pipelines
• Build APIs and services to integrate machine learning capabilities into enterprise applications
• Contribute to the development and evolution of the organisation’s ML platform and infrastructure

• Strong programming skills in Python
• Experience with machine learning frameworks such as PyTorch, Tensor Flow, or Scikit-learn
• Demonstrable experience deploying machine learning models into production systems
• Experience with Docker and Kubernetes for containerisation and orchestration
• Familiarity with MLOps tools such as MLflow, Kubeflow, Airflow, or similar
• Experience working with cloud platforms such as AWS, GCP, or Azure
• Strong understanding of data pipelines and large-scale data processing
• Experience with distributed data processing (e.g. Spark or Databricks)
• Knowledge of model monitoring and observability tools
• Experience building real-time inference systems or APIs
• Exposure to modern Generative AI or LLM frameworks

• Opportunity to work with a global professional services organisation delivering AI solutions to major clients
• Exposure to a wide range of industries and complex data challenges
• A collaborative, innovation-focused engineering environment
• Competitive salary and benefits package
• Flexible working arrangements (remote/hybrid)
• Strong opportunities for career development within a growing AI practice