Role Title:Senior Machine Learning Operations Engineer (MLOps)
Location:London, Farringdon (Hybrid)
Royal Mail delivers more than our competitors put together. Yet we have ambitious plans to grow market share both at home and globally, whilst transforming our UK operation to increase efficiency and profit. Our strategy clearly sets out these plans – data and technology is pivotal to its success.
In this role you’ll play a crucial part in executing the strategic roadmap for data and analytics. Drawing on the latest technical innovations, you will enable data-driven decision-making across Royal Mail to deliver value for our customers, our people, and our shareholders.
You will work with and lead the technical direction of multi-disciplinary project and programme teams to contribute to the development and successful execution of Royal Mail’s data strategy. You will provide technical analytical expertise and mentorship to colleagues to lead usage and implementation of machine learning operations capability, refining data policies and best practices where appropriate. You will ensure that we deliver business value from our data assets.
What will you do?
- Design, develop, and implement MLOps pipelines for the continuous deployment and integration of ML models
- Collaborate with data scientists to understand model requirements and optimise deployment processes
- Automate the training, testing and deployment processes for machine learning models
- Monitor and maintain models, ensuring optimal performance, accuracy and reliability
- Implement best practices for version control, model reproducibility and governance
- Optimise machine learning pipelines for scalability, efficiency and cost-effectiveness
- Troubleshoot and resolve issues related to model deployment and performance
- Ensure compliance with security and data privacy standards in all MLOps activities
- Keep up-to-date with the latest MLOps tools, technologies and trends
What skills and experience should you have?
- Strong understanding of machine learning principles and model lifecycle management
- Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn
- Knowledge of CI/CD pipelines, automation tools and version control systems like Git
- Strong problem-solving skills and ability to troubleshoot complex issues
- Experience with monitoring tools and practices for model performance in production
- Ability to work collaboratively in cross-functional teams
- Experience with Google Cloud Platforms and their respective machine learning services
- Familiarity with containerisation and orchestration tools such as Composer and Kubernetes
- Knowledge and understanding of cloud data platform architecture, infrastructure, maintenance, and optimisation
What we offer you…
- 18% Bonus
- Car allowance (or cash alternative)
- Hybrid Working (typically 3 days in office)
- 25 days holiday (plus the option to buy more)
- Plus, many more benefits!
Interview process and next steps…
We aim to move as quickly as possible! If your application is successful, you will be contacted by one of our recruitment team who will discuss the two-stage interview process with you.
Royal Mail is proud of our diverse employee network groups and the active role they play to support belonging and encourage a positive work environment. We are firmly committed to inclusion and passionate about our people representing the communities we serve.
We are happy to support your need for any adjustments during the application and hiring process. Please share the details within your application if required.
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