Full-timeWorkplace Type: HybridCompany DescriptionLinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.Join us to transform the way the world works.Job DescriptionThis 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 spacesBuilding platforms that support multiple AI-driven applications and agentsTranslating ambiguous natural language into precise, structured representationsDesigning systems that combine symbolic structure with learned representationsThis 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 experiencesBuild shared infrastructure and platforms that enable multiple AI-driven applications and agentic workflowsDesign and implement evaluation frameworks to measure quality, relevance, consistency, and grounding of AI system outputsDevelop 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.QualificationsBasic QualificationsBA/BS Degree in Computer Science, Machine Learning or related technical discipline, or related practical experience.2+ years experience in machine learning or AI engineering.2+ years experience in design and development of algorithmic solutions2+ years experience with programming languages such as Java, Python, etc.Preferred Qualifications4+ years of hands‑on experience in large-scale model training, model-system co‑design, or large AI systems.PhD in Computer Science, Machine Learning, or related technical discipline with a focus on advanced AI/ML techniquesProven experience in building and optimizing large-scale AI/ML models using frameworks such as PyTorch, PySpark, and CUDA.Several recent publications in top AI conferences on relevant areas including but not limited to Large Scale Model Training and LLM Algorithm Optimization, deep learning, reinforcement learning, foundation models etc.Expertise in distributed training, model parallelism, and hardware acceleration for AI workloads, including GPUs and TPUs.Demonstrated ability to solve complex AI challenges in large-scale environments, optimizing models for efficiency and scalability.Strong proficiency in AI system design, model optimization, and the development of production-quality AI pipelines.Published work in AI research or a significant contribution to industry-leading AI technologies.Suggested SkillsGenerative AI (GAI)Agentic systemsAI Research and DevelopmentDistributed AI Systems and Model ParallelismAdditional InformationGlobal Data Privacy Notice for Job CandidatesPlease follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
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