Senior Machine Learning Engineer - Platform Data Services at LinkedIn3

This role will be based in Dublin, Ireland.  Our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. We are seeking a Senior Machine Learning Engineer to help build the next generation of AI-powered systems that understand, reason over, and act on complex user intent. You will work on foundational capabilities that enable agentic experiences, semantic understanding, and large-scale AI-driven decision systems. These systems translate natural language into structured representations, power intelligent workflows, and continuously evolve as new concepts emerge. This role sits at the intersection of Generative AI, retrieval systems, and large-scale distributed infrastructure. You will help define the architecture and direction for how AI systems operate at scale, balancing flexibility, accuracy, and trust. You’ll work on problems such as: • Enabling AI systems to reason, retrieve, and act across large, evolving data spaces • Building platforms that support multiple AI-driven applications and agents • Translating ambiguous natural language into precise, structured representations • Designing systems that combine symbolic structure with learned representations This is a highly cross-functional role with the opportunity to shape how AI systems are built, evaluated, and deployed across a wide range of products and experiences.   A successful candidate will be comfortable operating at the intersection of AI research and engineering.  You will collaborate with a world-class team of researchers and engineers to develop and advance the next generation of AI models to push the boundaries of AI at scale.  Responsibilities: • Research, design, and develop large-scale foundation AI models, with a focus on LLMs, transformer architectures. • Develop retrieval and ranking systems (e.g., embedding-based retrieval, reranking, hybrid approaches) to support high-quality, low-latency AI experiences • Build shared infrastructure and platforms that enable multiple AI-driven applications and agentic workflows • Design and implement evaluation frameworks to measure quality, relevance, consistency, and grounding of AI system outputs • Develop and maintain scalable AI pipelines, optimizing training and inference workflows to handle vast amounts of data. • Collaborate with cross-functional teams of machine learning engineers, infrastructure engineers, and product teams to deliver impactful AI innovations across LinkedIn's products.