Principal Investigator in Applied AI/ML (BOSTON)
Company: Takeda Pharmaceutical
Location: Boston
Posted on: March 25, 2026
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Job Description:
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application process with Takeda will commence and that the
information I provide in my application will be processed in line
with Takeda’s Privacy Notice and Terms of Use. I further attest
that all information I submit in my employment application is true
to the best of my knowledge. 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 don't. 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, we'd 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 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. 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 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. 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: Boston, MA U.S. Base Salary Range:
$137,000.00 - $215,270.00 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 job. 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.
Locations Boston, MA Worker Type Employee Worker Sub-Type Regular
Time Type Job Exempt Yes It is unlawful in Massachusetts to require
or administer a lie detector test as a condition of employment or
continued employment. An employer who violates this law shall be
subject to criminal penalties and civil liability.
Keywords: Takeda Pharmaceutical, Manchester , Principal Investigator in Applied AI/ML (BOSTON), Science, Research & Development , Boston, New Hampshire