JOB DESCRIPTION:

Royal Canin is undergoing a significant Digital Transformation journey. Our ability to solve the most critical problems across Mars in a User Centric way through Data & Analytics is fundamental to our growth ambition and transformation. Significant early success in this journey, and the introduction of many critical foundational capabilities, means that we are looking to accelerate our ability to solve problems and ultimately drive value for Mars Inc.
The opportunities are significant for Mars, and the opportunities for those working in this space are both hugely exciting and rewarding. Connecting and deriving break-through insight from our Royal Canin and Petcare data ecosystems, leveraging the rapidly growing world of external data to get closer to our customers and consumers than ever before, and unlocking efficiencies and automation across our End-To-End Value Chain.
Building on this momentum, we are recruiting a Machine Learning and AI Engineering Lead to join our Royal Canin Global Data & Analytics Team who will accelerate the shaping and delivery of our Data & Analytics Agenda.
The Machine Learning and AI Engineering Lead will oversee ML and AI solution development and deployment as a capability served across the end-to-end Data & Analytics solution portfolio. The role integral to the organization’s mission of leveraging advanced technologies to drive innovation and efficiency across the organisation. The role will work closely with the Data Science Lead to develop and execute an AI and ML roadmap aligned with business goals and requirements.

• Serve as the technical lead for Generative AI and machine learning model deployment within RC D&A.
• Collaborate with the Data Science team to design, prototype and build next generation ML and AI products and accelerators.
• Design, architect and review technical architecture for data science, machine learning and AI solutions and provide feedback for optimal implementation.
• Develop and oversee the implementation of an MLOps and LLMOps strategy. Align and contribute towards the wider Petcare MLOps strategy.
• Review code developed by the data science team to ensure solution can be deployed. Identify opportunities to optimize methodologies.
• Contribute to a high performing data science function through coaching data scientists and providing training on writing scalable code and good software engineering practices.
• Create repeatable, interpretable, dynamic and scalable model training pipelines that are incorporated into analytic data products through cloud web applications and APIs.
• Define key performance indicators (KPIs) and implement monitoring systems for deployed products to ensure continuous operational performance. Define strategy to handle incident management.
• Engage with RC D&A Platform Lead and Platform Product Owner to scope, plan and implement accelerators.
• Stay updated with the latest advancements in MLOps. Apply relevant techniques into projects. Educate D&A on technological advancements in this area.
• Documentation: Maintain comprehensive documentation for model training pipelines, deployment processes, and code.
• Partner with the Product Management squad model and provide advice on how inflight projects can utilise ML and AI to generate additional value.