Senior Scientist, Bispecific/Multispecific Antibody Engineer

Manifold Bio is a dynamic biotech company building a pipeline of  targeted biologics using a novel in vivo-centric discovery approach. Our drug discovery engine is differentiated by massively parallel screening in vivo from the beginning of our discovery process. This unique platform is powered by a proprietary protein barcoding technology that allows multiplexed protein quantitation at unprecedented scale and sensitivity. We combine this and other high-throughput protein engineering approaches with computational design to create antibody-like drugs and other biologics. Our world-class team of protein engineers, biologists, and computational scientists are working together to aim the platform at therapeutic opportunities where precise targeting is the key to overcoming clinical challenges.

Manifold Bio is seeking a creative and driven Bispecific/Multispecific Antibody Engineer to join our protein engineering team and help expand the frontiers of shuttle-enabled drug delivery. In this role, you will drive innovative projects to engineer multispecific antibodies for precise tissue and cell targeting. You'll develop combinatorial screening methodologies and rational design approaches for selecting optimal binder pairs to target different antigens. You’ll also leverage Manifold's unique in vivo screening platform to test multispecific designs. This position is central to advancing internal therapeutic programs and building datasets that support partnering and platform expansion. You'll generate critical data for cross-functional program teams and serve as a core protein engineering team member, bringing strong antibody engineering expertise and collaborative skills to develop Manifold's next generation of targeted biologics.

Responsibilities

• Think deeply about and drive projects to engineer effective multispecific antibodies (including biparatopics, AND- and OR-gates, etc) for precise tissue and cell type targeting.
• Generate and deeply characterize individual binders to inform bispecific design strategies.
• Develop and test hypotheses about target and binder pairings to identify optimal therapeutic combinations.
• Develop and implement library-based or high-throughout methodologies for combinatorial screening of binders for bispecific designs in vitro.
• Utilize Manifold’s in vivo multiplexing capabilities to optimize multispecifics for precision targeting in vivo.
• Generate, interpret, and communicate high-quality, decision-enabling data to inform program strategy and therapeutic design.
• Collaborate cross-functionally to progress therapeutic programs.
• Maintain clear documentation, share findings in team meetings, and contribute to strategic discussions on program direction and platform development.

Required Qualifications

• PhD or equivalent experience in protein biochemistry, molecular biology, biological engineering, or related field.
• Proven expertise in antibody engineering with particular emphasis on bispecific/multispecific antibody development.
• Strong background in library-based biomolecule engineering and optimization techniques.
• Proficiency in standard molecular biology and biochemistry laboratory techniques.
• Strong analytical skills and creative problem-solving abilities, with the capacity to develop novel approaches and drive innovation in complex scientific challenges.
• Adaptable and proactive mindset with a track record of productivity and successfully translating innovative ideas into meaningful outcomes.
•  Strong communication skills and collaborative working style.

Preferred Qualifications

• Industry experience developing therapeutic antibodies
• Previous experience working on brain shuttle technologies
• Hands-on experience with protein characterization techniques, particularly Octet
• Background working with NGS data and DNA/protein sequence analysis
• Experience with display technologies and selections including phage, yeast, and/or ribosome display platforms
• Familiarity with computational protein engineering methods, machine learning applications, or biophysical modeling approaches

We value different experiences and ways of thinking and believe the most talented teams are built by bringing together people of diverse cultures, genders, and backgrounds.