Research Scientific Director, Large Molecule AI Development

Takeda-posted 3 days ago
Full-time • Director
Hybrid • Boston, MA
5,001-10,000 employees
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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. 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.

  • 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)
  • 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
  • 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.
  • 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
  • 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
  • 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.
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