Research Scientist, AI/ML Agentic Systems

Takeda • Boston, MA

1d • $116,000 - $182,270 • Hybrid

About The Position

We are seeking a Research 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. This role requires a unique combination of expertise in large language models, agentic frameworks, and understanding of drug discovery processes. You will translate standard research workflows into agentic frameworks, develop new agent skills, and deploy systems that augment scientist productivity across Computational Sciences and Global Research.

Requirements

• PhD in Computer Science, Computational Biology, Bioinformatics, or related field
• 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.

Nice To Haves

• 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 ap

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) that extend agentic capabilities to specialized scientific domains including 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 (RAG) 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.

Benefits

• U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others.
• U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree