Role - Machine Learning Engineer
Location Hybrid, 1 day on site in London (with flex)
Salary - £70,000 to £75,000
The Opportunity
Were partnering with a client in the financial services sector who are looking to bring on a Machine Learning Engineer to their growing Intelligent Automation Team of 50. Following a period of significant transformation and with a recently refreshed executive leadership team, the business has bold ambitions and a clear mandate to move quickly. A key part of this journey is the Intelligent Automation function, which is delivering AI and GenAI-driven optimisation across core services. This is a fantastic chance to join a growing team where your work will be visible, meaningful and directly improve how customers and internal teams are supported.
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).
The Role
Reporting to the Machine Learning Lead, youll be a hands-on Machine Learning Engineer with a strong track record of building and deploying ML solutions at scaleparticularly 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.
The Person
Were looking for someone who combines strong engineering fundamentals with practical ML delivery experience, and who enjoys working collaboratively in agile teams.
Youll 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.
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