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Nautilus Biotechnology is developing a single-molecule protein analysis platform designed to democratize access to the proteome and accelerate drug development. The company is pursuing hard scientific problems with an entrepreneurial mindset to enable precision and personalized medicine.
As Scientist II, Antibody Engineering & Characterization, you will drive the engineering and characterization of antibody probes central to the Nautilus single-molecule proteomics platform. You will own antibody characterization, generating data that determines which candidates advance downstream. Beyond managing a rapidly growing probe pipeline, you will apply mechanistic studies and binding characterization to improve probe discovery cycles. You will integrate sequence, structural, and biophysical data to identify properties that predict on-platform performance and translate those insights into rational design rules.
Key responsibilities include:
- Apply protein engineering, antibody discovery, and affinity maturation strategies to design antibody variants with improved binding affinity
- Perform antibody purification, screening, and characterization using techniques such as BLI, SPR, DSF, SEC/SEC-MALS, Simple Western, and ELISA to validate engineering outcomes
- Identify, evaluate, and implement new technologies and methods for antibody characterization and performance
- Apply AI/ML and in silico tools (protein language models, generative design, structure prediction) to guide affinity maturation; generate and prioritize variant designs, translate model outputs into testable panels, and feed experimental data back into models to drive iterative design-build-test-learn cycles
- Coordinate and perform screening of antibodies on the Nautilus platform, analyze results, and integrate on-platform performance with off-platform characterization data
- Interpret and communicate data clearly, translating complex results into actionable recommendations for prioritization and go/no-go decisions
- Collaborate closely with bioinformatics, computational biology, discovery, and assay development teams to formulate hypotheses, experimental priorities, and success criteria
- Contribute to experimental strategy and project planning, proactively identifying risks and proposing alternative approaches
- Present findings and document methods, results, and conclusions in electronic lab notebooks and technical reports
- Foster a collaborative, knowledge-sharing environment by providing scientific input to peers and sharing best practices
REQUIREMENTS:
- PhD in protein engineering, structural biology, biochemistry, or related field plus 2–3 years of relevant industry experience
- Direct hands-on experience characterizing antibodies and protein-protein interactions using BLI, SPR, Western blot, ELISA, and/or other biophysical methods; preferably experience measuring antibody binding to short linear peptides or epitopes
- Hands-on experience developing, troubleshooting, and fine-tuning assays across multiple technologies (SPR, BLI, ELISA, Western blot, etc.)
- Protein engineering experience using structural or computational insight to design and test antibody variants (e.g., rational mutagenesis, affinity engineering)
- Experience with structure-prediction and modeling tools
PREFERRED QUALIFICATIONS:
- Experience applying AI/ML or computational methods (protein language models, generative design, structure-based deep learning) to guide antibody affinity maturation and translating model output into testable variant designs
- Familiarity with Python and ML frameworks or computational structural biology pipelines
- Familiarity with antibody discovery platforms (phage display, yeast display, ribosome display)
- Experience with proteomics platforms
