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Job Description

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.

We are seeking a strategic, visionary Research Scientific Director to lead the next generation of AI/ML-enabled biologics discovery at Takeda. This senior leadership role has two primary mandates:

Drive AI/ML application to accelerate and de-risk large-molecule pipeline projects Build and scale AI/ML platform capabilities as a core competitive advantage for biologics discovery.

You will be a key leader within the AI/ML organization, setting strategy, building partnerships across R&D, and delivering measurable impact on our biologics portfolio. You will be accountable for converting state-of-the-art AI/ML science into validated, production-grade decision tools that change how Takeda discovers, designs, and optimizes large-molecule therapeutics.

This role requires a leader who can operate at multiple altitudes, defining long-term vision and roadmaps while also ensuring scientific rigor, technical depth, and operational excellence in execution.

Key Responsibilities

1. AI/ML Application to Pipeline Projects

• Drive the AI/ML strategy for antibody and other large-molecule discovery programs from target assessment through lead optimization.
• Ensure AI/ML activities are aligned with program and portfolio goals, with clear milestones, timelines, and success criteria.
• Deliver production-grade decision tools (for example, variant ranking, developability risk flagging, zero-shot design) that are seamlessly integrated into discovery workflows.
• Act as a hands-on technical leader across multiple programs:
  • Define modeling strategies and architectures
  • Prioritize methods and experiments
  • Review and challenge scientific output for quality and robustness
• Partner with Discovery Platform Heads and project leaders to embed AI/ML milestones into program plans, stage-gates, and decision forums (discovery, engineering, mult-specifics)

2. AI/ML Platform Build and Innovation

• Define and own a multi-year platform roadmap for large-molecule AI/ML capabilities, including models, tools, data assets, and infrastructure.
• Lead the development and deployment of foundational models for antibody and protein sequence, structure, and function prediction.
• Drive integration of physics-based methods (for example, MD, FEP, docking) with machine learning approaches to create hybrid models with improved accuracy and generalization.
• Own data strategy for large-molecule AI/ML (data requirement, quality standard, governance)
• Partner closely with engineering, computational, and laboratory teams to ensure the platform is usable, reliable, and scalable across programs and sites

3. Leadership, Talent, and Culture

• Build, mentor, and retain a high-performing, multidisciplinary team of scientists and engineers.
• Provide clear goals, expectations, and development paths and ensure high standards of scientific excellence and reproducibility.
• Champion an inclusive, collaborative, and learning-oriented culture that values curiosity, rapid iteration, and rigorous validation.
• Communicate complex AI/ML concepts and results clearly to non-experts, including project teams and senior leadership, enabling data-driven decision-making.

Qualifications

Required:

• PhD degree in Computational Biology, Bioinformatics, Computer Science, or a related field with 10+ years relevant experience
• Proven track record of leading AI-driven projects in a research pharmaceutical setting.
• Significant depth of expertise in at least one field relevant to the job (for example, machine learning, biotherapeutic design, etc.).
• Demonstrated experience in modeling antibody/ antigen sequence, structure and interaction.
• Significant depth of expertise in at least one relevant area, such as:
  • Machine learning or deep learning
  • Protein or biotherapeutic design
  • Structural modeling or computational biophysics
• Strong analytical and problem-solving skills, with demonstrated creativity and the ability to contribute both individually and through teams
• Versatile communicator who can explain complex ideas to non-specialists and influence diverse stakeholders

Preferred:

• Experience leading teams that integrate machine learning with physics-based modeling (for example, MD, FEP, docking)
• Experience building or owning AI/ML platforms or foundational models used across multiple programs
• Prior leadership of cross-functional initiatives spanning discovery biology, protein engineering, and data or engineering teams

ADDITIONAL INFORMATION

• The position will be based in Cambridge, MA.  This position is currently classified as “hybrid” by Takeda’s Hybrid and Remote Work policy

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:

$174,500.00 - $274,230.00

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

Full time

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.