Scientist II, Antibody Engineering

Astellas Pharma • Burlingame, CA

2d • $105,280 - $150,400 • Onsite

About The Position

Astellas is seeking a scientist to contribute to and lead antibody engineering projects within its global Antibody Engineering group in the Biologics Engineering unit in South San Francisco. The role supports AI-enabled antibody design and data workflows across the South San Francisco and Japan sites. The scientist will establish, operate, and improve scalable workflows that combine external SaaS platforms, internal computational methods, AI agents, and biologics data management to accelerate global antibody discovery programs and broaden adoption by experimental scientists.

The role applies computational capabilities and experimental data to discover and engineer differentiated therapeutic antibodies and advance programs toward lead optimization and clinical candidate selection. The scientist will work with experimental teams and cross-functional collaborators to move therapeutic candidates from discovery toward preclinical stages, and will coordinate with CROs and external technology providers. The position is based in South San Francisco and requires on-site work.

Requirements

• PhD with 2 or more years of relevant experience, or MS with 7 or more years of relevant experience, in computational protein or antibody design, machine learning, bioinformatics, structural biology, computational biology, biophysics, or a related field.
• Demonstrated experience in computational antibody design and/or AI/ML-enabled protein design, including generative and structure-prediction models such as ProteinMPNN, RFdiffusion, ESMFold, IgFold, or equivalent tools.
• Experience may include target-conditioned binder design and optimization of modalities such as monoclonal, bispecific, or multi-specific antibodies, TCEs, ADCs, or other engineered biologics using protein language models and structural modeling tools.
• Demonstrated understanding of antibody discovery and engineering, including relationships among antibody sequence, structure, binding, function, format, and developability.
• Ability to interpret experimental antibody data and translate results into testable design hypotheses and molecule-prioritization decisions.
• Excellent communication skills and ability to articulate computational and experimental plans and present research findings and recommendations in meetings.
• Strong work ethic and proactive approach to identifying and addressing gaps in computational design, data, and workflow capabilities.
• Strong collaborative mindset and ability to work with global project teams, including teams in South San Francisco and Japan.
• Willingness to take on tasks and responsibilities as needed in a dynamic environment and support multiple antibody discovery programs.

Nice To Haves

• Experience establishing, operating, or improving computational workflows for protein or antibody design.
• Experience with AI-enabled SaaS platforms, AI agents, and/or biologics data management platforms.
• Background in oncology research or strong interest in applying antibody engineering to oncology, with familiarity in AI/ML-driven tumor-targeting biologics and de novo antibody design for challenging oncology targets.
• Related industry experience in computational antibody or protein engineering, AI-based sequence generation, bioinformatics, structural biology, or molecular modeling for biologics developability.
• Experience with commercial or cloud-based AI-enabled antibody or protein design platforms and biologics data management systems.
• Experience with antibody generation or screening technologies, such as phage display, yeast or mammalian display, B-cell discovery, immunization-based discovery, or related experimental platforms.
• Experience coordinating work with CROs, external technology providers, or global research teams, including cross-site collaboration.

Responsibilities

• Plan, design, develop, and optimize mono-, bi-, and multi-specific antibodies using generative AI and machine-learning models, including computational de novo sequence generation and in silico optimization.
• Establish and operate scalable workflows using AI-enabled SaaS platforms, internal computational methods, and AI agents, collaborating with experimental teams on protein production, validation, and characterization.
• Use iterative design-make-test-learn cycles to support antibody discovery, lead optimization, and candidate selection.
• Promote dissemination and adoption of AI-enabled antibody design and related computational workflows across teams.
• Collaborate with cancer biology, translational science, clinical development, AI/ML, research informatics, data management, and global Biologics Engineering colleagues, including teams in South San Francisco and Japan.
• Provide computational design, data, and biologics data management support for antibody engineering and discovery programs across both sites.
• Coordinate with CROs and external technology providers, including outsourced protein production and analytics providers and research collaborators.
• Integrate computational recommendations with binding, functional, biophysical, and developability data to inform program decisions.
• Evaluate and integrate new antibody engineering and AI/ML technologies, including AI-enabled SaaS platforms, AI agents, and biologics data management systems.
• Establish reproducible, user-friendly workflows that can scale across programs.
• Present findings and recommendations to internal stakeholders and at scientific conferences.
• Document computational workflows and design decisions and contribute to publications and patent applications.

Benefits

• Medical, dental, and vision insurance
• Generous paid time off options, including vacation and sick time, plus national holidays including year-end shutdown
• 401(k) match and annual company contribution
• Company-paid life insurance
• Annual corporate bonus and quarterly sales incentive for eligible positions
• Long-term incentive plan for eligible positions
• Company fleet vehicle for eligible positions
• Referral bonus program

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level