Currently tracking 14 active AI roles, up 295% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $129k–$203k (avg $166k).
| Title | Stage | AI score |
|---|---|---|
| Senior Scientist, Agentic AI and Machine Learning (PDMB) 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. | Agent | 8 |
| Senior Specialist, Data Science 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. |
| 8 |
| Senior Specialist, Data Scientist 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. | Post-train | 7 |
| Sr. Specialist – Business Insights & Analytics, Advanced Analytics - US Vaccines & ID 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. | AgentData | 7 |