We’re First Central Insurance & Technology Group (First Central for short), an innovative, market-leading insurance company. We protect the things customers love so they can get on with what matters to them in life.
Data drives us. It fuels our outstanding distribution, finance, technology and legal services. Our underwriting skills are built on data expertise; it creates the insights we need to give the right cover to the right customers at the right price. But, it’s the people inside and outside our business that power us. They make us stand out, help us succeed. We’re ambitious. We’re growing. We’ve won awards.
We’re big on data: it gives us the insights we need to give the right cover to the right customers at the right price. But it’s the people inside our business that power us and were looking for two Machine Learning Operation Engineers to join our Technology and Data teams in these newly created roles.
Our Machine Learning Operations (MLOps) Engineers will play a significant role within our Data Function, were you’ll work on the design and implementation of machine learning model engineering frameworks, solutions, and best practices. The ideal candidate will be technically proficient in machine learning and its applications, able to demonstrate an understanding of data management, and show a keen interest in keeping up with industry trends, you’ll 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 be expected to 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.
We’re based in Haywards Heath, West Sussex, Salford Quays, Manchester, Guernsey, and Gibraltar, we love hybrid working, so you'll spend most of your time working from home and will only attend the office for team meetings (around once a month) but of course, it’s your choice - if you prefer to be in the office more - that's good with us too.
You’ll be the perfect person for us if:
- You’re passionate about bridging the gap between data science and operations, and you're adept at developing and maintaining machine learning models in a production environment.
- You excel at designing, implementing, and maintaining continuous integration, continuous delivery, and continuous deployment pipelines for machine learning applications.
- You have experience with machine learning lifecycle management tools like MLflow and are familiar with data version control.
- You are a problem solver with a keen eye for detail and a strong commitment to teamwork, eager to collaborate with cross-functional teams to ensure the smooth deployment and scalability of machine learning systems.
Powering the business with the right tools
- Contribute to the design and implementation of Machine Learning Engineering standards and frameworks.
- Support model development, with an emphasis on auditability, versioning, and data security.
- Implement automated data science model testing and validation.
- Assist in the optimisation of deployed ML model scoring code in production services.
- Assist in the design and implementation of data pipelines and engineering infrastructure to embed scaled machine learning solutions.
- Using CI/CD pipelines, manage the deployment and version management of large numbers of data science models (Azure DevOps).
- Support the implementation of Machine Learning Ops on cloud (Azure & Azure ML. Experience with Databricks is advantageous.)
- Protect against model degradation and operational performance issues through the development and continual automated monitoring of model execution and model quality.
- Manage automatic model retraining within a production environment.
- Engage in group discussions on system design and architecture, sharing knowledge with the wider engineering community.
- Collaborate closely with data scientists, data engineers, architects, and the software development team.
- Liaise with stakeholders across the business to ensure ML is being used to improve strategic business decisions and identify new areas for improvements.
- 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 & knowledge
- 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).
- Demonstratable 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.
Skills & Qualifications
- 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.
- Strong stakeholder management.
- 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’re 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. To get a taste of the advantages you’ll enjoy, take a look at all our perks in full here.
Intrigued? Our Talent team can tell you everything you need to know about what we want and what we’re offering, so feel free to get in touch.