Senior AI Developer role focused on designing and delivering enterprise-grade AI solutions, including generative AI and RAG-based systems. The role involves hands-on development, integration of LLMs and vector databases, optimization, and adherence to engineering best practices within a cross-functional team.

Senior Manager, GenAI & Agentic AI Tech Lead at Merck, responsible for driving the delivery and integration of GenAI and automation capabilities within Global Support Functions. This hands-on role involves technical solution design, architecture, writing production code, building and deploying services, and ensuring operational stability for end-to-end GenAI and agentic AI solutions. The role requires collaboration with various teams, continuous refinement of RAG architectures, design of agentic workflows, and implementation of testing and observability.

This role focuses on designing, delivering, and optimizing Quality Management capabilities on the Veeva Vault QMS platform, with a significant emphasis on integrating AI and Agentic AI use cases within a regulated healthcare environment. Responsibilities include leading QMS transformation programs, delivering AI/Agentic AI solutions for classification, root cause analysis, risk prediction, and document review, managing DevOps pipelines, performing hands-on configuration and validation, and stakeholder management. The role requires experience with Veeva QMS, product management, and implementing AI/Agentic AI solutions in a GxP compliant manner.

This role focuses on the design and delivery of enterprise-grade AI solutions, specifically generative AI and RAG-based components. The individual contributor will implement, integrate, and optimize AI systems, working with LLMs, vector databases, and retrieval components. The role emphasizes hands-on development, collaboration with cross-functional teams, and adherence to engineering best practices within an Agile framework.

This role focuses on assessing AI systems for risks, recommending mitigations and guardrails, and testing AI models, agents, and systems for performance, safety, security, and explainability. It involves supporting the development and implementation of AI ethics policies and processes, and staying updated on AI developments and regulations within the healthcare domain. The role requires experience in AI ethics, trust and safety, and risk management, with a preference for hands-on coding experience in AI/ML and knowledge of XAI and regulatory landscapes.

This role is for an intern in Applied Data Science & AI focused on Quality Improvement within the Animal Health division at Merck. The intern will develop AI-based tools to help colleagues in Quality teams work more efficiently and effectively on problem-solving and process improvement. Responsibilities include exploring AI applications, building tools, training colleagues, and providing fresh perspectives. The role requires a 4th-year HBO student in Applied Data Science & ICT, with a 5-6 month commitment.

AI Engineer role at Merck focused on building and deploying AI solutions, particularly RAG and generative AI applications, within healthcare R&D, manufacturing, and commercial operations. The role involves coding, DevSecOps, API development, and staying current with AI advancements.

Solution Architect role focused on designing and evaluating enterprise-level architectures for Data & Analytics, Intelligent Automation, and AI, including GenAI and machine learning lifecycles. The role involves collaborating with teams, monitoring trends, and ensuring seamless integration and compliance within a regulated healthcare environment.