Sr. Scientist, AI/ML Biologics

Job Description 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. We aim to apply AI and machine learning across the entire drug discovery process, from target identification through development. Our team brings together computational scientists, biologists, engineers, and drug hunters to tackle hard problems and shape how AI delivers real impact in drug discovery. Position Overview We are seeking an innovative and dynamic AI/ML scientist with a passion for leveraging AI/ML in antibody discovery and design to join our Large Molecule AI/ML team. This role will be an embedded member of multidisciplinary project teams, integrating advanced computational methods with cutting‑edge experimental strategies to advance biologics programs from discovery through candidate nomination and toward clinical development. The ideal candidate will have a strong background in computational biology, machine learning, and structural modelling, with demonstrated application of AI/ML in biologics discovery and optimisation. Key Responsibilities Develop and implement state‑of‑the‑art AI/ML methodologies for antibody design and discovery. Develop, implement, and deploy advanced machine learning algorithms for the multi‑parameter optimisation of biologics with a focus on delivering high‑quality development candidates (antibodies, antigens, ADCs, and other modalities). Build tools to incorporate data from integrated Design‑Predict‑Make‑Confirm cycles with automated experimental platforms generating quality data at scale needed for project‑specific and foundational models. Innovate, develop, and apply predictive models for protein design and developability engineering, utilising large‑scale NGS, in‑vitro, in‑vivo and other proprietary in‑house and external data sources. Actively contribute as a core member of cross‑functional project teams, partnering closely with biology, protein engineering, and data generation teams to drive programmes toward candidate selection and IND‑enabling stages. Manage and process large‑scale biological datasets for model training and evaluation. Stay abreast of advancements in NLP, ML, and generative AI to build novel tools that enhance therapeutic discovery and development. Collaborate with internal experts to optimise the computational discovery infrastructure, offering both individual and team‑based innovative solutions. Communicate complex scientific ideas effectively to both technical and non‑technical audiences, fostering collaboration across multidisciplinary teams and influencing project decisions. Qualifications PhD degree in a scientific discipline (or equivalent) with 2+ years relevant experience, or MS with 8+ years relevant experience, or BS with 10+ years relevant experience. Proven track record in developing machine learning models for chemical and biological data, including AI/ML‑enabled molecular generation and affinity prediction. Demonstrated experience in modelling antibody/antigen sequence, structure and interaction. Proficiency in programming languages such as Python and experience with cloud computing capabilities. Strong analytical and problem‑solving skills, with demonstrated creativity and the ability to contribute individually and collaboratively in fast‑paced project team environments. Versatile communicator who can elucidate complex ideas to non‑specialists and commitment to continuous improvement and innovation. Demonstrated learning agility, and scientific curiosity while maintaining focus on driving greater impact in the face of uncertainty and change. Strong problem‑solving aptitude and strategic thinking with an entrepreneurial mindset. Experience analysing NGS‑derived antibody repertoires for sequence‑ and structure‑based design. Preferred Qualifications & Skills Experience developing or applying modern ML architectures for antibody design models (LLMs, diffusion models, flow‑matching, Bayesian optimisation, GNNs, etc.). Experience designing de‑novo binders for specified targets and epitopes. Experience with molecular simulation and conformational analysis techniques. 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 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, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licences 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 programme, 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, colour, 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. Job Exempt Yes #J-18808-Ljbffr Initial Therapeutics, Inc.