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First Central

Senior Machine Learning Operations Engineer

Posted 24 Days Ago
Be an Early Applicant
In-Office or Remote
3 Locations
Senior level
In-Office or Remote
3 Locations
Senior level
The Senior Machine Learning Operations Engineer will design and implement ML frameworks, manage lifecycle of ML models, and enhance data pipelines in collaboration with various teams.
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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!

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 and outside our business that power us and were currently on the hunt for 2 experienced Senior Machine Learning Operation Engineers to join our Data Function.

You’ll 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’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’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 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’ve 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 organizational 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’ll accept applications for remote workers! We offer great flexibility in working patterns and a company-wide culture to be proud of.

Core skills were looking for to succeed in the role:

  • 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
  • You’ll be 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

Powering the business with the right tools

What’s involved:

  • 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.

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

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

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.

Top Skills

Azure Devops
Azure Ml
Azure Stream Analytics
Cognitive Services
Data Factory
Databricks
Docker
Event Hubs
Kubernetes
Azure
Python
PyTorch
Synapse
TensorFlow

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