AI/ML Engineer – Recommendation Systems & Personalisation (Contract to Hire)

Company DescriptionBionesca Ltd. is a cutting-edge data platform dedicated to revolutionising the future of skin health. By leveraging advanced technologies, Bionesca provides data-driven solutions to deliver personalised skincare recommendations. Our mission is to empower individuals with insights and tools to achieve optimal skin health. Role DescriptionWe are looking for an AI/ML Engineer to help design and improve our personalisation and recommendation systems.This role focuses on bringing data-driven rigour and intelligent decision-making into our platform, improving how we generate, rank, and optimise recommendations for users.You will work closely with the founder and engineering team to build scalable, high-quality personalisation systems, combining domain logic, data, and AI techniques.This is a highly applied role for someone who enjoys solving real product problems using practical machine learning approaches.QualificationsDesigning and improving recommendation and personalisation systemsDeveloping and refining scoring, ranking, and decision-making frameworksEvolve machine learning models where they add meaningful valueWork with structured and unstructured data (user inputs, product data, model outputs)Define and track metrics to evaluate recommendation quality and performanceCollaborate with engineering to integrate models into production systemsImprove the system through continuous iteration and data-driven insightsLeveraging modern AI approaches, including LLMs where appropriate, to enhance system capabilitiesMust have requirements:3–6+ years of experience in applied AI/ML or data-driven product developmentStrong understanding of recommendation systems, ranking, or personalisationKeen ness to work in a dynamic startup environment with a can do attitude and not shy away from taking on varied responsibilitiesSelf-starter who want to own and shape a critical part of a productSolid foundation in machine learning and model evaluationExperience working with real-world data and production systemsStrong proficiency in Python and modern ML toolingAbility to translate ambiguous problems into clear, structured solutionsExperience integrating ML into real products, not just experimentsStrong ownership mindset and ability to operate in a fast-moving environment

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