Research Sr. Scientist, AI/ML Agentic Systems

Position Overview We are seeking a Research Sr. Scientist to develop agentic AI systems that transform how drug discovery research is conducted. As part of the AI/ML Foundation team, you will build autonomous AI agents capable of reasoning, planning, and executing complex scientific workflows—from literature synthesis and target identification to experimental design and data analysis. The role demands expertise in large language models, agentic frameworks, and a deep understanding of drug discovery processes. Key Responsibilities Develop agentic AI systems for drug discovery applications including target‑disease association, automated literature search and synthesis, hypothesis generation, and intelligent design of experiments. Translate standard research workflows into agentic frameworks—decomposing complex scientific processes into autonomous agent tasks that can reason, plan, execute tools, and iterate based on results. Design and implement new agent skills (tools, functions, APIs) to extend agentic capabilities to specialized scientific domains such as molecular design, property prediction, assay planning, and data analysis. Build agentic systems that integrate with foundation models and external knowledge sources for autonomous hypothesis generation, evidence retrieval, and scientific reasoning. Develop retrieval‑augmented generation pipelines connecting agents to internal and external scientific literature, databases, and experimental results. Partner with research scientists to understand workflow needs, validate agent outputs, and iterate on system design to ensure scientific rigor and utility. Stay current with advances in agentic AI, LLM applications, and scientific automation; contribute to internal knowledge sharing and external publications. Qualifications Required: PhD in a scientific discipline (or equivalent) with 2+ years relevant experience, or MS with 8+ years, or BS with 10+ years. Experience with large language models (GPT, Claude, Llama) and their application to complex reasoning tasks. Proficiency in Python and experience with agentic AI frameworks (LangChain, AutoGen, CrewAI, or similar). Experience building RAG systems, including vector databases, embedding models, and retrieval pipelines. Understanding of drug discovery processes and scientific research workflows. Strong problem‑solving skills and ability to translate complex scientific processes into computational workflows. Preferred: Experience in pharmaceutical or biotech R&D environments. Background in biology, chemistry, or disease biology. Experience with reinforcement learning or planning algorithms for agent decision‑making. Familiarity with scientific databases (PubMed, UniProt, ChEMBL) and APIs. Experience deploying AI systems in production environments. Track record of publications or presentations on LLM or agentic AI. Additional Information Location: Cambridge, MA. This position is classified as "hybrid" under Takeda’s Hybrid Work policy. Compensation & Benefits U.S. Base Salary Range: $137,000.00 – $215,270.00. U.S. employees may be eligible for short‑term and/or long‑term incentives, medical, dental, vision insurance, a 401(k) plan with company match, disability benefits, basic life insurance, tuition reimbursement, paid volunteer time off, company holidays, and well‑being benefits. U.S. employees are also eligible to receive up to 80 hours of sick time and accrue up to 120 hours of paid vacation. EEO Statement Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law. #J-18808-Ljbffr Takeda Pharmaceuticals International GmbH