Senior Machine Learning Operations Engineer in London

Location: Guernsey, Haywards Heath, Home Office (Remote) or Manchester

Salary: £65,000 - £75,000 - depending on experience

Department: Technology and Data

We are 1st Central, a market-leading insurance company utilising smart data and technology at pace. Rapid growth has been based on giving our 1.4 million customers exactly what they want: great value insurance with an excellent service.

You will play a significant role within our Data Function, working on the design and implementation of machine learning model engineering frameworks, solutions, and best practices. You will be technically proficient in machine learning and its applications; you will demonstrate an understanding of data management and show a keen interest in keeping up with industry trends. You will work closely with different teams such as Data Science, Data Engineering, Architecture, and Software Development to ensure efficient operation and use of Data Science models and will facilitate the full life cycle of machine learning models from data ingestion, model development, testing, validation, deployment, to monitoring and retraining of models within different environments.

If you have a strong understanding of Microsoft Azure, fluency in data science coding, and expertise in MLOps frameworks, we want to hear from you. Bring your excellent communication, problem-solving, and organisational skills to our team and help us drive innovation and excellence.

This is a flexible hybrid working role with occasional visits to our offices, when required, in either Salford Quays, Manchester, Haywards Heath, West Sussex, or Guernsey. If you live further afield, we will accept applications for remote workers! We offer great flexibility in working patterns and a company-wide culture to be proud of.

• A strong understanding of Microsoft Azure (Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory)
• Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc.
• Skilled in application of MLOps frameworks within a production environment
• Excellent communication skills, both verbal and written
• Strong time management and organisation skills
• Ability to diagnose and troubleshoot problems quickly
• Excellent problem-solving and analytic skills

• You will contribute to the design and implementation of Machine Learning Engineering standards and frameworks.
• You will support model development, with an emphasis on auditability, versioning, and data security.
• You will implement automated data science model testing and validation.
• You will assist in the optimisation of deployed ML model scoring code in production services.
• You will assist in the design and implementation of data pipelines and engineering infrastructure to embed scaled machine learning solutions.
• You will use CI/CD pipelines, manage the deployment and version management of large numbers of data science models (Azure DevOps).
• You will support the implementation of Machine Learning Ops on cloud (Azure & Azure ML). Experience with Databricks is advantageous.
• You will protect against model degradation and operational performance issues through the development and continual automated monitoring of model execution and model quality.
• You will manage automatic model retraining within a production environment.
• You will engage in group discussions on system design and architecture, sharing knowledge with the wider engineering community.
• You will collaborate closely with data scientists, data engineers, architects, and the software development team.
• You will liaise with stakeholders across the business to ensure ML is being used to improve strategic business decisions and identify new areas for improvements.
• You will adhere to the Group Code of Conduct and Fitness and Propriety policies, Company Policies, Values, guidelines, and other relevant standards/regulations at all times.

• Experience in developing and maintaining production ML systems, including automatic model retraining and monitoring of production models.
• Deploying Infrastructure as Code (IAC) across various environments such as dev, uat and prod.
• Handling large volumes of data in various stages of the data pipeline, from ingestion to processing.
• Proven experience with feature stores, using them for both offline model development and online production usage.
• Building integrations between cloud-based systems using APIs, specifically within the Azure environment.
• Practical knowledge of agile methodologies applied in a data science and machine learning environment.
• Designing, implementing, and maintaining data software development lifecycles, with a focus on continuous integration and deployment (CI/CD).
• Demonstrable expertise in machine learning methodology, best practices, and frameworks.
• Understanding of microservices architecture, RESTful API design, development, and integration.
• Basic understanding of networking concepts within Azure.
• Familiarity with Docker and Kubernetes is advantageous.
• Experience within financial/insurance services industry is advantageous.
• Experience with AzureML and Databricks is advantageous.

• Strong understanding of Microsoft Azure (Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory).
• Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc.
• Skilled in application of MLOps frameworks within a production environment.
• Excellent communication skills, both verbal and written.
• Strong time management and organisation skills.
• Ability to diagnose and troubleshoot problems quickly.
• Excellent problem-solving and analytic skills.

• Embrace, embed and incorporate the company values.
• Self-motivated and enthusiastic.
• An organised and proactive approach.
• Ability to work on own initiative and as part of a team.
• A flexible approach and positive attitude.
• Strives to drive business improvements to contribute to the success of the business.

This is just the start. Imagine where you could end up! The journey's yours ...

What can we do for you? People first. Always. We are passionate about our colleagues and know the best people deserve an extraordinary working environment. We owe it to them so that’s what we offer. Our workplaces are energetic, inspirational, supportive.

Intrigued? Our Talent team can tell you everything you need to know about what we want and what we are offering, so feel free to get in touch.