Antibody Engineering Scientist/ Senior Scientist

Oxford BioTherapeutics•San Jose, CA

50d•Onsite

About The Position

This is your opportunity to join our Antibody Discovery Team at OBT! We’re looking for a scientist who enjoys collaboration and brings strategic thinking and creativity to complex challenges. If you’re passionate about driving scientific excellence and ready to make an impact, we’d love to hear from you. About Oxford Biotherapeutics Oxford BioTherapeutics (OBT) is a clinical-stage biotechnology company developing antibody therapeutics for the treatment of cancer. You will play an integral role in the pre-clinical development of novel immuno-oncology therapeutics. Our OGAP® platform is the world's largest, cancer specific, membrane protein library, directly measuring plasma membrane protein expression in patient tumors. OGAP is used to identify novel, highly tumor specific antigens for novel first-in-class ADC, Bispecific T-cell Engager (BITE®) and Chimeric Antigen Receptor (CAR) targets. Our lead asset, OBT076, is an Antibody Drug Conjugate (ADC) in Phase 1b clinical development. Our clinical and pre-clinical pipeline of novel biologics is balanced between internal programs, focused on ADCs and checkpoint regulators, and externally partnered programs with key innovators in oncology such as Roche, Boehringer Ingelheim and Zymeworks. Purpose of the Role We are seeking a highly motivated and innovative Scientist to drive the discovery and optimization of mAbs and multi-specific antibody formats. This role will spearhead sequence and structure-guided protein engineering initiatives, leveraging cutting-edge AI/ML tools and display technologies to enhance antibody affinity, specificity, stability, and developability. The ideal candidate will combine deep technical expertise with strategic vision, fostering an open and collaborative research culture. This is a lab-based role, and candidates must be willing to work onsite 5 days a week.

Requirements

PhD. in Molecular Biology, Biochemistry, or related discipline.
7+ years of relevant industry experience in therapeutic antibody engineering OR exceptional postdoctoral training.
Must have experience with display technologies (phage, yeast, or mammalian display).
Expert in library creation, selection, and enrichment analysis
Proven track record in affinity maturation, antibody developability, multi-specific optimization and library-based engineering.
Expertise in structure-guided protein engineering
Deep knowledge of antibody structure-function relationships and protein engineering strategies.
Hands-on experience with display technologies (phage, yeast, mammalian) and developability characterization (DSF/DSC-light, DLS, SEC).
Working knowledge of AI/ML tools for protein structure prediction and optimization

Nice To Haves

Engineering and optimizing bi- or multi-specific antibody formats, T-cell engagers, ADCs, and other complex biologics is highly desirable.
Experience with antibody humanization, affinity maturation, and optimization of antibody developability for therapeutic applications is preferred.
Experience in engineering conditionally active antibodies (e.g., pH-dependent variants for enhanced low-pH binding, peptide masking technologies) and knowledge of payload conjugation strategies for ADCs would be advantageous.

Responsibilities

Design, engineer, and optimize antibodies to improve binding affinity, specificity, stability, and developability.
Lead affinity maturation and developability campaigns using directed-evolution and sequence & structure-based design.
Develop, screen and validate display library-based workflows.
Develop and validate affinity binding assays (SPR), interpret complex kinetic and affinity datasets, and integrate findings into project decisions.
Engineer conditionally active antibody variants (e.g., enhanced binding at low pH, cleavable peptide masks)
Humanize mouse antibodies
Familiar with protein structure modeling tools, such as PyMol.
Experience in affinity-tuning monoclonal antibodies to achieve high, medium, or low binding affinities.
Define and oversee end-to-end protein engineering workflows, ensuring resource efficiency, timeline adherence, and risk management.
Mentor and guide scientists, setting high standards for data quality and fostering career development.
Collaborate cross-functionally with Antibody Discovery, Protein Sciences, Bioinformatics, AI, and Project Management teams.
Cultivate a collaborative, data driven, and innovative research culture aligned with company goals.
Work with AI scientists to optimize antibody properties (affinity, specificity, developability) and use display technologies to test, optimize, and select final leads.
Leverage AI/ML-enabled structural tools for modeling and hypothesis generation.
Drive continuous improvement of workflows and methodologies.