Job Title: Senior Machine Learning Engineer

Location: London

Department: Media Agency

Job Overview

As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building and optimising a Machine Learning system for Advert Classification. We are looking for a Machine Learning leader who is competent across modern ML tooling, methodologies and design practices, whilst also being able to design hybrid systems that integrate LLMs.

The Machine Learning lead is expected to lead the ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in the delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives and as a result the ML Lead is expected to drive the strategy and operationalise automatic machine evaluation with metrics and best-practice MLOps.

You will partner with Data Scientists and Software Engineers, to ensure the system is reliable, performant and production-ready. You will also contribute to engineering excellence, across Machine Learning and MLOps, by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain.

Key Responsibilities

• Lead the design and build of high-quality, scalable and reusable Machine Learning systems using Sainsbury’s engineering standards and best practices.
• Design and optimise Machine Learning modules for Advert classification, applying the ML-Lifecycle and best practice in model selection and development.
• Lead the design and implementation of supporting Machine Learning Operations, applying best in class approaches to data versions, model re-training and data observability.
• Implement automation tools and frameworks for experiment tracking, data and model observability to streamline the deployment and monitoring of machine learning models in production.
• Lead the system evaluation methodology, including the evaluation strategy, data generation and evaluation metrics.
• Provide guidance to mid Data Scientists on best practice and methodological choices, when optimising machine learning modules and the system, overall.
• Provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth.
• Collaborate and support with data scientists across the lifecycle, including EDA, data transformation, model selection, feature engineering, model selection.
• Optimise data processing workflows and storage solutions to improve performance and reduce costs.
• Work closely with cross-functional teams, including software engineering, and product management, to deliver data solutions that meet business needs.
• Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews.
• Innovation and Continuous Improvement: Foster a collaborative and inclusive team environment that encourages continuous learning and improvement.