Job Title: ML/AI Engineering Lead (Azure)
Location: London (Hybrid)
Salary: £100,000 + Bonus
An organisation with a mature Data & Analytics function is seeking a Machine Learning & AI Engineering Lead to drive the design, development, and deployment of advanced ML and AI solutions. This role sits at the heart of their mission to leverage cutting-edge technology to unlock innovation, efficiency, and scalable impact.
You will partner closely with Data Science leadership to shape and execute the AI/ML roadmap while building robust engineering foundations that enable high-quality, production-ready products across the business.
Technical Leadership
- Serve as the technical lead for Generative AI and machine learning deployment across the organisation.
- Architect, design, and review scalable solutions for ML, AI, and data science use cases.
- Develop and oversee the implementation of MLOps and LLMOps strategies, aligning with wider enterprise standards.
Collaboration & Delivery
- Partner with the Data Science team to prototype, build, and productionise next-generation AI/ML products and accelerators.
- Review and improve code developed by data scientists to ensure it is deployment-ready, robust, and scalable.
- Engage with platform leadership and product owners to scope, plan, and deliver accelerators and platform capabilities.
Operational Excellence
- Build repeatable, interpretable, and scalable model-training pipelines integrated into cloud apps and APIs.
- Define KPIs and implement monitoring systems to ensure reliable performance of deployed models.
- Create and maintain documentation for training pipelines, deployment workflows, and engineering best practices.
- Provide coaching and technical development to data scientists, promoting strong engineering practices.
Innovation & Thought Leadership
- Stay up to date with advancements in MLOps, LLMOps, and cloud-native AI practices.
- Promote and educate teams on emerging technologies and their potential applications.
- Advise product teams on how ML/AI can enhance ongoing initiatives and deliver additional value.
Experience & Capability
- 5–7 years in a quantitative, ML-focused, or AI engineering role, ideally within CPG, retail, or similarly fast-paced industries.
- Proven experience delivering production-level AI/ML solutions using scalable, reusable codebases and modern cloud tooling.
- Strong understanding of MLOps and DevOps frameworks, including CI/CD, model lifecycle management, testing, and monitoring.
- Hands-on familiarity with Azure technologies such as AzureML, Azure AI Foundry, and Databricks.
Skills & Mindset
- Ability to translate business needs into analytical and engineering frameworks.
- Strong communication skills with the ability to influence stakeholders across technical and non-technical teams.
- Customer-centric approach, especially with internal stakeholders, ensuring high adoption and value realisation.
- Strategic thinker with problem-solving capabilities and a growth mindset.
- Comfortable operating in a dynamic, evolving, high-velocity environment.