Senior Machine Learning Operations Engineer

Were 1st Central a market-leading insurance company utilising smart data and technology h has been based on giving our 1.4 million customers exactly what they want: great value insurance with an excellent service. And thats the same for our colleagues too; we won Insurance Employer of the Year at the British Insurance Awards 2024 and our Glassdoor score is pretty mega too!

Were big on data: it gives us the insights we need to give the right cover to the right customers at the right price. But its our people inside and outside the business who truly power us. Were currently on the hunt for an experienced Senior Machine Learning Operations Engineer to join our Data Function.

Youll play a significant role within our Data & Analytics Function working on the design and implementation of machine learning model engineering frameworks solutions and best practices. Youll be technically proficient in machine learning and its applications; youll demonstrate an understanding of data management and show a keen interest in keeping up with industry trends. Youll work closely with different teams such as Data Science Data Engineering and Software Development to ensure efficient operation and use of Data Science models.

You 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.

This is a flexible hybrid role with occasional visits to our offices in Salford Quays (Manchester) or Haywards Heath (West Sussex) when required. For those based further afield we also welcome applications from remote UK based workers
. We offer excellent flexibility in working patterns and a company wide culture you can be proud to be part of.

If you possess a strong understanding of applying MLOps frameworks in production combined with a data engineering background and experience in Databricks and PySpark we want to hear from you.

Core skills were looking for to succeed in the role:

Data Science & Programming Skills
:
Fluency in Python and modelling frameworks such as PyTorch and Tensor Flow.

ML Ops Expertise
:
Youll be skilled in deploying and managing Machine Learning Models within a production environment.

Analytical & Problem-Solving: Excellent problem-solving and analytical skills with the ability to diagnose and troubleshoot problems quickly.

Organisational

Skills:

Strong time management and organisational abilities experience working to tight deadlines.

Communication & Collaboration
:
Excellent communication skills both verbal and written ability to collaborate effectively with cross-functional teams.

Whats involved:

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

Job-specific competencies

• 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 life cycles with a focus on continuous integration and…