Merck

Director of foundational AI at Merck, leading a team of ML researchers and engineers to develop and train large multi-modal foundation models and bespoke methods for biological data analysis. The role involves providing technical guidance, interpreting results, and publishing research findings, with a focus on advancing therapeutic strategies. Requires a PhD and significant experience in ML/AI, team leadership, and training large models.

Senior Scientist role focused on developing, benchmarking, and deploying agentic AI and Machine Learning solutions within the healthcare domain (Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics). The role involves partnering with scientists, integrating AI/ML into R&D platforms, and contributing to responsible AI practices. Requires hands-on experience with LLMs, agent frameworks, multimodal datasets, and model evaluation.

Senior AI/ML Scientist role at Merck focused on developing and deploying next-generation computational toxicology capabilities. The role involves leading projects, building production-grade models and agentic systems, and establishing governance and MLOps practices for preclinical research in a regulated environment. Key responsibilities include fine-tuning foundation models, integrating multimodal datasets, and collaborating with cross-functional teams.

Senior Specialist, Digital Reg Docs Tech Lead at Merck, focusing on developing and integrating Generative AI solutions within R&D enterprise applications. The role involves designing, building, and maintaining production GenAI systems and data pipelines, with a strong emphasis on end-to-end model integration, data engineering, and application development in a regulated healthcare environment. Responsibilities include prompt engineering, fine-tuning, implementing retrieval approaches, building data pipelines, integrating models into applications, and establishing ML Ops workflows, while mentoring team members and ensuring compliance.

Senior AI Research Scientist at Merck in Prague, focusing on research, assessments, and technical evaluations of AI models and frameworks to solve problems and enhance generative AI capabilities. The role involves conducting feasibility studies, creating proof of concepts, and leading smaller projects, with an emphasis on applying AI to internal problems and datasets within the biopharmaceutical domain.

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.

Seeking a Scientist, MCICC to drive innovation in AI-powered drug evaluation and development. This role focuses on building and optimizing advanced AI systems, including large language models (LLMs) and molecular generation and property prediction models. The ideal candidate will combine deep technical expertise with domain knowledge in pharmaceutical R&D, enabling rapid iteration and deployment of cutting-edge solutions.

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.

AI Research Scientist with 1-2+ years of experience in healthcare IT, focusing on research, assessments, and technical evaluations of AI models and frameworks to solve internal problems and enhance generative AI capabilities. The role involves creating proof-of-concepts, staying updated on AI research, and mentoring colleagues. Requires a strong understanding of AI research landscape, hands-on Python development, and familiarity with GenAI, deep learning, NLP, CV, and ML frameworks, preferably within a cloud environment.

Senior Specialist, DevOps Engineer responsible for building and maintaining MLOps workflows, CI/CD pipelines, and cloud infrastructure (AWS, Kubernetes) for generative AI applications, including LLM-based authoring tools, machine translation, RAG pipelines, and embedding services. The role focuses on operational excellence, reliability, security, and compliance in a regulated healthcare environment.

Seeking a Senior Specialist, Data Scientist for Merck's R&D Quality Assurance Analytics & Tech Systems team. The role involves developing and maintaining innovative data science and analytics solutions, including machine learning and generative AI models, to support the QA space within the R&D Division. Responsibilities include technical support for data science requests, developing analytics solutions using tools like PowerBI and SQL, becoming a subject matter expert in R&D Quality Data, communicating insights, and identifying opportunities for Generative AI implementation. The role also includes mentorship and contributing to the internal data science community.

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 and impacts, recommending mitigations and guardrails, and testing/evaluating AI models, agents, and systems for performance, safety, security, and explainability. It involves developing and implementing policy processes and staying updated on AI developments and regulations within the healthcare domain.

Merck is seeking a computational biologist with expertise in image analysis to join their Translational Genome Analytics research team. The role involves applying AI/ML-based analytics to large multi-omics imaging and functional genomics datasets for target and biomarker discovery in drug development, with a focus on Oncology. The candidate will collaborate with cross-functional teams and contribute to quantitative analysis of imaging datasets and integration of machine learning with phenotypic screens.

This role focuses on applying advanced analytics, Machine Learning, NLP, Generative AI, and Agentic AI frameworks to generate actionable insights for commercial decisions in the pharmaceutical/biotech/healthcare industry. It involves leveraging LLMs, RAG, autonomous agents, and multi-agent orchestration to enhance insight generation and automate analytical workflows, with a secondary focus on data engineering for these applications.

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 focuses on ensuring AI projects at Merck are developed and deployed responsibly, with a strong emphasis on risk mitigation, ethical considerations, and rigorous testing and evaluation of AI models and systems. It involves consulting with stakeholders, developing policies, and staying abreast of regulatory changes within the healthcare domain.