Research Senior Scientist AIML – Agentic Systems

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Job Description

At Takeda we are a forward-looking world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on three therapeutic areas and other targeted investments we push the boundaries of what is possible to bring life-changing therapies to patients worldwide.

The AI/ML organization at Takeda is building a team to transform how medicines are discovered. Our goal is to apply AI and machine learning across the entire drug discovery process not just isolated steps but as an integrated approach from target identification through development. This requires discernment: knowing which models and methods fit each problem and the creativity to adapt when they dont. We work with foundational models generative approaches and autonomous systems but the tools only matter when paired with people who understand the science deeply enough to use them well. Our team brings together computational scientists biologists engineers and drug hunters. If you want to contribute your expertise to hard problems alongside colleagues with different perspectives and help shape how AI delivers real impact in drug discovery wed like to hear from you.

Position Overview

We are seeking Senior Scientists 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 workflowsfrom 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.

Accountabilities:

• 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 frameworksdecomposing 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.

Educational & Requirements:

• PhD in Computer Science Computational Biology Bioinformatics or related field with 2 years relevant experience OR MS with 6 years relevant experience.
• Strong 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 ap

Additional Competencies Common in Strong Candidates

• Ability to lead cross-functional initiatives and mentor junior scientists.
• Experience in translating computational insights into experimental strategies.
• Strong publication record or demonstrated thought leadership in AI for biology and molecular design.
• Comfort working in fast-paced innovation-driven environments with evolving priorities.

ADDITIONAL INFORMATION

• The position will be based in Cambridge MA

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees and we strive to be more transparent with our pay practices.

For Location:

U.S. Base Salary Range:

The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors including the qualifications of the individual applicant for the position years of relevant experience specific and unique skills level of education attained certifications or other professional licenses held and the location in which the applicant lives and/or from which they will be performing the actual base salary offered will be in accordance with state or local minimum wage requirements for the job location.

U.S. based employees may be eligible for short-term and/ or long-term incentives. 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.

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.

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