Machine Learning Engineer MLOps Python LLM AWS

About the Role

As a Machine Learning Engineer, you will lead the Machine Learning activities within the Insights and Data Analytics Team from conception to deployment, creating and scaling high-impact models that solve core product challenges. You'll define the Machine Learning roadmap from a technical perspective, evaluating model architectures, optimising data pipelines and ensuring that ML features provide actionable insights within the product. This isn't just about training models; it's about building the ML infrastructure that enables the business to iterate and scale with confidence.

You will be working at a SaaS FinTech company whose capital market tools are used by Investment Banks and independent research providers to automate and analyse client service and research consumption, presenting a complete overview of the client relationship made available via the Cloud.

Responsibilities

• Lead Machine Learning activities from conception to deployment.
• Create and scale high-impact models to solve product challenges.
• Define the Machine Learning roadmap from a technical perspective.
• Evaluate model architectures and optimise data pipelines.
• Ensure ML features provide actionable insights within the product.
• Build and maintain ML infrastructure for business iteration and scaling.
• Collaborate and provide technical leadership to a small team.

Requirements

• Experienced Machine Learning Engineer who prioritises system reliability, latency and observability as much as model accuracy.
• Strong Python skills and experience of leveraging the AWS stack to move models from development environments to robust production services.
• Strong MLOps experience.
• Comfortable designing high-throughput APIs, managing data and implementing solutions.
• Experience training, deploying and supporting non-LLM models as well as supporting LLM Services in a production environment.
• Strong knowledge of software engineering best practices including TDD and Pair Programming.
• Collaborative, comfortable mentoring others, providing technical direction and communicating with senior stakeholders.
• Achieved a 2.1 or above in a STEM discipline.

Location / WFH

You can work from home most of the time, meeting up with colleagues in the London office once a month for team collaboration and meetings.