Senior Machine Learning Engineer

Overview

In this role you lead the design, build, and optimization of a scalable ML system for advert classification, shaping the ML roadmap within a media-focused team. You’ll oversee end-to-end ML lifecycle, guide data scientists, and implement MLOps practices to ensure production-ready performance. You’ll collaborate with software engineers and product management to deliver impactful data solutions, while driving innovation in data engineering and ML workflows. This is a hands-on leadership position with a strong emphasis on measurable evaluation and system reliability.

Pay / Benefits

• colleague discount at group brands
• pensions scheme
• life cover
• performance-related bonus up to 20%
• annual holiday allowance with option to buy extra
• private healthcare

Responsibilities

• Lead the design and build of scalable ML systems following engineering standards
• Design and optimise ML modules for advert classification using ML lifecycle best practices
• Lead ML operations, including data versions, retraining, and data observability
• Implement automation for experiment tracking, data/model observability, and deployment monitoring
• Define system evaluation methodology, data generation, and evaluation metrics
• Mentor mid-level data scientists and provide guidance on ML modules and system improvements
• Collaborate with data scientists, software engineers, and product management throughout the lifecycle
• Optimize data processing workflows and storage to improve performance and reduce costs
• Promote knowledge sharing through tech workshops, code reviews, and team collaboration
• Drive innovation and continuous improvement in ML and MLOps, aligning with Sainsbury’s values
• Lead by example in communication, accountability, and engineering excellence
• Support spikes, POCs, and early investigative work
• Help establish technical roadmap and best practices across ML workflows

Key requirements

• 6–10 years of experience designing and building end-to-end ML systems with strong MLOps experience
• Strong understanding of modern ML methodologies and data science concepts
• Proven experience integrating LLMs as hybrid AI-ML systems
• Academic background with at least a Bachelor’s in Computer Science
• Desirable: experience in modern computer vision and end-to-end image detection systems
• Strong deployment and management of ML on cloud platforms, specifically MS Azure and AWS
• Strong analytical and problem-solving skills
• Excellent communication skills for non-technical stakeholders
• Ability to work independently and in cross-functional teams

• strong communication
• leadership and mentoring
• collaborative mindset
• ML lifecycle and MLOps
• data observability and experiment tracking
• LLM integration and hybrid AI systems

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