Takeda Digital Ventures
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Sr. Scientist, AI/ML
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Takeda Digital Ventures 1 week ago Be among the first 25 applicants Join to apply for the
Sr. Scientist, AI/ML
role at
Takeda Digital Ventures Get AI-powered advice on this job and more exclusive features. Job Level: Senior Travel: Minimal (if any)
At Takeda, we strive to provide transformational opportunities for every member of our team, and we empower our people to take charge of their futures. In an environment that fosters lifelong learning and a growth mindset, you’ll have the support you need to thrive — at work and beyond.
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Job ID
R0160065
Date posted
08/05/2025
Location
Boston, Massachusetts
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’sPrivacy Noticeand 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
Position Overview
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 our core therapeutic areas and pioneering AI-driven platforms, we aim to accelerate the next generation of biologics discovery.
We are seeking an innovative and dynamic
Senior Scientist
with a strong background in
computational biology, structural bioinformatics, and machine learning , particularly as applied to
antibody and large molecule design . You will join our Large Molecule AI/ML team and contribute to a multidisciplinary group that integrates
state-of-the-art AI with experimental strategies
to drive therapeutic breakthroughs in oncology, neuroscience, and inflammatory diseases.
This execution-focused role will involve applying AI/ML and structural modeling techniques to design, optimize, and validate biologics, including antibodies, enzymes, and antibody-drug conjugates (ADCs).
Key Responsibilities
Develop and implement AI/ML models for sequence- and structure-based design of biologics, with emphasis on generative frameworks (e.g., diffusion models, inverse folding, LMs). Apply and extend tools such as Boltz, Rosetta, AlphaFold2, ESMFold, ProteinMPNN, and other foundational models for de novo antibody discovery, affinity maturation, and developability optimization. Build and optimize predictive models for multiple objectives (e.g., solubility, immunogenicity, thermostability, epitope specificity) based on NGS, in vitro, and in vivo datasets. Integrate 3D structural data into model-guided protein design pipelines. Collaborate with experimental scientists to inform hypothesis generation, model validation, and iterative learning in Design–Make–Test–Analyze cycles. Manage and process large-scale experimental and synthetic datasets for model training, benchmarking, and deployment. Prototype and deploy ML pipelines using best practices in software engineering and reproducibility Stay current with the latest developments in NLP, structural modeling, and AI for protein science; evaluate emerging tools for integration. Clearly communicate complex ideas to technical and non-technical audiences and contribute to internal knowledge sharing.
Required Qualifications
PhD degree in Computational Biology, Structural Biology, Machine Learning, or related fields (or equivalent) with 2+ years relevant experience, or MS with 8+ years relevant experience, or BS with 10+ years relevant experience Demonstrated ability to build and apply ML models (deep learning, protein LMs, GNNs) to biological or structural datasets. Hands-on experience with antibody design or protein engineering, especially using ML-guided or structure-aware methods. Strong understanding of protein structure and dynamics, including MD simulation, FEP, Rosetta modeling, or AlphaFold-based tools. Proficiency in Python and ML libraries (e.g., PyTorch, scikit-learn, NumPy); familiarity with Unix command line tools and scripting. Strong data wrangling and visualization skills; ability to translate modeling outputs into actionable insights for bench scientists. Excellent interpersonal and written communication skills; thrives in a highly collaborative environment.
Preferred Qualifications
Experience developing or fine-tuning generative models for protein design (e.g., RFdiffusion, ProGen, ESM-IF, ProteinMPNN). Prior application of structure-guided ML to engineer antibodies, antigens, or binders against defined epitopes. Familiarity with large-scale structural datasets (PDB, EMDB) and bioinformatics tools for sequence/structure analysis. Exposure to wet-lab data integration and cross-functional collaboration with experimental biologists. Experience building reproducible workflows using Docker/Singularity, Nextflow, or similar tools. Understanding of biologic drug properties (developability, immunogenicity, CMC constraints).
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-termincentives. 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.
Apply Now
Back to nav Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
Job function Research, Analyst, and Information Technology Industries Venture Capital and Private Equity Principals Referrals increase your chances of interviewing at Takeda Digital Ventures by 2x Get notified about new Senior Scientist jobs in
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Sr. Scientist, AI/ML
role at
Takeda Digital Ventures 1 week ago Be among the first 25 applicants Join to apply for the
Sr. Scientist, AI/ML
role at
Takeda Digital Ventures Get AI-powered advice on this job and more exclusive features. Job Level: Senior Travel: Minimal (if any)
At Takeda, we strive to provide transformational opportunities for every member of our team, and we empower our people to take charge of their futures. In an environment that fosters lifelong learning and a growth mindset, you’ll have the support you need to thrive — at work and beyond.
Back to nav
Job ID
R0160065
Date posted
08/05/2025
Location
Boston, Massachusetts
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’sPrivacy Noticeand 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
Position Overview
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 our core therapeutic areas and pioneering AI-driven platforms, we aim to accelerate the next generation of biologics discovery.
We are seeking an innovative and dynamic
Senior Scientist
with a strong background in
computational biology, structural bioinformatics, and machine learning , particularly as applied to
antibody and large molecule design . You will join our Large Molecule AI/ML team and contribute to a multidisciplinary group that integrates
state-of-the-art AI with experimental strategies
to drive therapeutic breakthroughs in oncology, neuroscience, and inflammatory diseases.
This execution-focused role will involve applying AI/ML and structural modeling techniques to design, optimize, and validate biologics, including antibodies, enzymes, and antibody-drug conjugates (ADCs).
Key Responsibilities
Develop and implement AI/ML models for sequence- and structure-based design of biologics, with emphasis on generative frameworks (e.g., diffusion models, inverse folding, LMs). Apply and extend tools such as Boltz, Rosetta, AlphaFold2, ESMFold, ProteinMPNN, and other foundational models for de novo antibody discovery, affinity maturation, and developability optimization. Build and optimize predictive models for multiple objectives (e.g., solubility, immunogenicity, thermostability, epitope specificity) based on NGS, in vitro, and in vivo datasets. Integrate 3D structural data into model-guided protein design pipelines. Collaborate with experimental scientists to inform hypothesis generation, model validation, and iterative learning in Design–Make–Test–Analyze cycles. Manage and process large-scale experimental and synthetic datasets for model training, benchmarking, and deployment. Prototype and deploy ML pipelines using best practices in software engineering and reproducibility Stay current with the latest developments in NLP, structural modeling, and AI for protein science; evaluate emerging tools for integration. Clearly communicate complex ideas to technical and non-technical audiences and contribute to internal knowledge sharing.
Required Qualifications
PhD degree in Computational Biology, Structural Biology, Machine Learning, or related fields (or equivalent) with 2+ years relevant experience, or MS with 8+ years relevant experience, or BS with 10+ years relevant experience Demonstrated ability to build and apply ML models (deep learning, protein LMs, GNNs) to biological or structural datasets. Hands-on experience with antibody design or protein engineering, especially using ML-guided or structure-aware methods. Strong understanding of protein structure and dynamics, including MD simulation, FEP, Rosetta modeling, or AlphaFold-based tools. Proficiency in Python and ML libraries (e.g., PyTorch, scikit-learn, NumPy); familiarity with Unix command line tools and scripting. Strong data wrangling and visualization skills; ability to translate modeling outputs into actionable insights for bench scientists. Excellent interpersonal and written communication skills; thrives in a highly collaborative environment.
Preferred Qualifications
Experience developing or fine-tuning generative models for protein design (e.g., RFdiffusion, ProGen, ESM-IF, ProteinMPNN). Prior application of structure-guided ML to engineer antibodies, antigens, or binders against defined epitopes. Familiarity with large-scale structural datasets (PDB, EMDB) and bioinformatics tools for sequence/structure analysis. Exposure to wet-lab data integration and cross-functional collaboration with experimental biologists. Experience building reproducible workflows using Docker/Singularity, Nextflow, or similar tools. Understanding of biologic drug properties (developability, immunogenicity, CMC constraints).
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-termincentives. 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.
Apply Now
Back to nav Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
Job function Research, Analyst, and Information Technology Industries Venture Capital and Private Equity Principals Referrals increase your chances of interviewing at Takeda Digital Ventures by 2x Get notified about new Senior Scientist jobs in
Boston, MA . Woburn, MA $130,000.00-$190,000.00 3 weeks ago Scientist/Sr. Scientist, Translational Development
Waltham, MA $175,000.00-$200,000.00 1 week ago Scientist - Process Research & Development
Cambridge, MA $156,000.00-$296,500.00 1 week ago Waltham, MA $160,000.00-$190,000.00 4 weeks ago Boston, MA $160,800.00-$241,200.00 4 days ago Boston, MA $281,300.00-$442,800.00 6 days ago Cambridge, MA $95,000.00-$105,000.00 1 month ago Sr./Principal Scientist, Computational Chemistry
Cambridge, MA $145,000.00-$200,000.00 3 weeks ago Computational Chemistry Senior Research Scientist
Boston, MA $123,400.00-$185,100.00 2 weeks ago Senior Scientist, Translational Development
Senior Scientist, Pharmaceutical Development CMC (CONTRACT)
Senior Scientist Translational Gene editing Development with AAV, Gene and Cell Therapeutics Platform Research Organization
Senior Materials Scientist Engineer - hydrophobic coating development
Principal Scientist, Drug Substance Process Development
Senior Scientist, Analytical Development - Drug Substance
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr