Senior Machine Learning Operations Engineer

1st Central; Haywards Heath; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading insurance company in the UK is seeking a Senior Machine Learning Operations Engineer to enhance its data and analytics function. This role will involve designing ML frameworks and supporting model development with a focus on automation and monitoring. Ideal candidates will have strong technical proficiency in MLOps, Databricks, and Azure, alongside excellent problem-solving skills. The position offers flexibility for remote work and an energetic company culture with numerous perks.

Benefits

Flexible working patterns

Company culture promoting well-being

Insurance benefits

Qualifications

• Comprehensive knowledge of cloud technologies in Azure.
• Fluency in Python and familiarity with ML frameworks like PyTorch and TensorFlow.
• Experience in developing and maintaining production ML systems.

Responsibilities

• Design and implement ML Engineering standards and frameworks.
• Support model development and ensure data security.
• Manage model retraining and monitor performance.

Skills

Databricks

PySpark

Azure

Python

MLOps frameworks

CI/CD pipelines

Cloud-based APIs

Docker

Kubernetes

Job description

Job Overview

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 our people inside and outside the business who truly power us. We’re currently on the hunt for an experienced Senior Machine Learning Operations Engineer to join our Data Function.

You’ll 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. You’ll be technically proficient in machine learning and its applications; you’ll demonstrate an understanding of data management and show a keen interest in keeping up with industry trends. 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.

Key Responsibilities

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

Qualifications

Core skills were looking for to succeed in the role: Technical Skills: Comprehensive knowledge of Databricks, PySpark, Microsoft Azure (Azure ML, Azure Stream Analytics, Cognitive Services, Event Hubs, Synapse, Data Factory). Data Science & Programming Skills: Fluency in Python and modelling frameworks such as PyTorch and TensorFlow. ML Ops Expertise: You’ll 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.

• 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.
• 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 organisational skills.
• Ability to diagnose and troubleshoot problems quickly.
• Excellent problem-solving and analytic skills.

Behaviours

• 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.

People first. Always. We’re passionate about our colleagues and know the best people deserve an extraordinary working environment. 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.

We’re 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. And that’s 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!