- Location
- London, England, United Kingdom · published
- Department
- Engineering
- Seniority
- Lead
- Source
- Workable
Description
Work on exciting public sector projects and make a positive difference in people’s lives. At Zaizi, we thrive on solving complex challenges through creative thinking and the latest tools and tech.
As a Machine Learning Engineer,AI, you’ll be responsible for researching, developing, and testing new AI algorithms, models, and technologies that businesses can use to automate tasks and gain insights from their data.
Key responsibilities include building complex models, designing and managing MLOps pipelines for CI/CD, monitoring, and model retraining. Mentoring junior members, influencing technical decisions within the team, and handling complex, non-routine problems.
Our work culture is inclusive, modern, friendly, and democratic. We look for bright, positive-thinking individuals with a can-do attitude. Our people enjoy challenging themselves to be the best at what they do – if that sounds like you, you'll fit right in!
Role Objectives
These are the expected objectives for this role. We are happy to discuss this further during the interview process with the successful candidate.
- Model Development & Delivery: Design, build, test, and deploy complex machine learning models, ensuring high standards of quality, performance, and scalabilityDecide what model is most suitable for use in products and services
- MLOps Pipeline Management: Design and manage robust MLOps pipelines, including continuous integration/continuous delivery (CI/CD), monitoring, and model retraining, to ensure efficient and reliable model deployment and operation
- Advanced Problem Solving: Act as a technical expert for complex, non-routine technical challenges within machine learning, developing and implementing innovative and effective solutions
- Customise, optimise, re-train and maintain existing models
- Deploy models into production, testing and assuring them to ensure they meet performance requirements
- Work with others to integrate models with existing systems
- Check that models used in live products and services stay safe, secure and continue to work effectively