Machine Learning Engineer

Reporting to the Machine Learning Lead, you'll be a hands-on Machine Learning Engineer with a strong track record of building and deploying ML solutions at scale-particularly in NLP and GenAI. You will:

• Design, develop and scale NLP and GenAI capabilities to optimise business processes.
• Build out a robust GenAI application technology stack, from experimentation through to production.
• Develop, maintain and improve existing ML pipelines, data transformation workflows and MLOps practices.
• Create serverless data/ML pipelines in cloud environments (Azure preferred).
• Work closely with architects, senior developers, product owners and business analysts to shape requirements, solution design and architecture.
• Own user stories end-to-end, contribute to sprint planning, and provide accurate estimates for delivery.
• Translate business problems into well-structured ML and automation solutions using data-led insight.
• Collaborate with wider technology teams to share knowledge, improve processes, and produce training/documentation.

We're looking for someone who combines strong engineering fundamentals with practical ML delivery experience, and who enjoys working collaboratively in agile teams. You'll bring:

• Strong Python development skills and solid grasp of algorithms, data structures and cloud concepts.

• Experience contributing to solution design and familiarity with architectural patterns/frameworks.

• Proven delivery of serverless pipelines in Azure/AWS/GCP (Azure highly desirable).

• Experience building data transformation pipelines using SQL and NoSQL databases.

• Hands-on ownership of CI/CD (Jenkins/Azure DevOps/GitHub Actions) and MLOps in Azure ML / Azure AI Foundry / SageMaker / Vertex AI.

• Working knowledge of Infrastructure as Code (Bicep, ARM, Terraform).

• A test-driven development mindset and commitment to engineering quality.

• Broad understanding of ML approaches, with the ability to explain methods clearly:

• Regression, clustering, decision trees, reinforcement learning

• Gradient boosting, CNNs, RNNs, LSTMs

• Attention models, encoder/decoder architectures, transformers, vector semantics

Demonstrable experience developing GenAI applications in real-world settings.

The confidence to communicate complex technical ideas to non-technical stakeholders.

Comfortable estimating work, breaking down requirements into tasks, and delivering in an agile environment. If you would like to learn more, please apply through the advert and we will be in touch to discuss in more detail.

This is a full-time role offering a salary of £70,000-£75,000 plus a strong benefits package. The position is hybrid, typically one day per week on site in London (with flexibility around which day).