Scientist II, Antibody Engineering and Characterization

At Nautilus, we have a big and important mission: improve the health of millions by unleashing the potential of the proteome to accelerate drug development and enable a new world of precision and personalized medicine. We are developing a single-molecule protein analysis platform of unprecedented sensitivity, scale, and ease of use that we believe will democratize access to the proteome – one of the most dynamic and valuable sources of biological insight. To accomplish this, we are pursuing hard scientific problems with an entrepreneurial mindset and creating a world-class team of builders, innovators, and dreamers across a wide range of disciplines.

Scope and Responsibilities

We are hiring for a Scientist II, Antibody Engineering & Characterization to join our growing team. This role will drive the engineering and characterization of the antibody probes that are central to our single-molecule proteomics platform. The Scientist II will own antibody characterization, generating data that determines which candidates advance downstream. Beyond keeping pace with a rapidly growing probe pipeline, this scientist will apply mechanistic studies and binding characterization to improve upon probe discovery cycles. They will integrate sequence, structural, and biophysical data to identify the properties that predict on-platform performance, and turn those insights into rational design rules. Working at the intersection of hands-on protein engineering and in silico design, they will shape our affinity maturation strategy and drive the success of the Nautilus platform.

Apply protein engineering, antibody discovery, and affinity maturation strategies to design antibody variants with improved binding affinity

Perform antibody purification, screening and characterization (e.g., BLI, SPR, DSF, SEC/SEC-MALS, Simple Western, ELISA etc.) to validate antibody engineering outcomes

Identify, evaluate and implement new technologies and methods for antibody characterization and performance

Apply AI/ML and in silico tools (e.g., protein language models, generative design, structure prediction) to guide antibody affinity maturation: generate and prioritize variant designs, translate model outputs into testable variant panels, and feed experimental binding and stability data back into the models to drive iterative design-build-test-learn cycles in partnership with computational biology and bioinformatics teams

Coordinate/perform screening of antibodies on the Nautilus platform, analyze and interpret the results, and integrate on-platform performance with off-platform characterization data

Interpret and communicate data clearly, translating complex results into actionable recommendations that inform 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, and to advance antibodies through the pipeline

Contribute to experimental strategy and project planning, proactively identifying risks, proposing alternative approaches, and adapting plans as new data emerge

Present findings in meetings and document methods, results, and conclusions in a clear, reproducible manner (e.g., electronic lab notebook, technical reports)

Foster a collaborative, knowledge-sharing environment by providing scientific input to peers, sharing best practices.

Qualifications

Direct experience characterizing antibodies and protein-protein interactions with BLI, SPR, Western blot, ELISA and/or other biophysical methods. Preferably, experience measuring binding of antibodies to short linear peptides or epitopes. Hands on experience developing, troubleshooting, and fine-tuning assays across multiple technologies such as SPR, BLI, ELISA, Westen 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

PhD in protein engineering, structural biology, biochemistry or related fields +2-3 years of relevant industry experience

Preferred qualifications

Experience applying AI/ML or computational methods (e.g., 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 (e.g., phage display, yeast display, ribosome display)

Experience with proteomics platforms

Nautilus Team Culture

We are determined to do whatever it takes to get our platform into the hands of researchers who will use it to upend the status quo in basic research and healthcare.

We work on cross functional teams, wear many hats, take risks to work through uncertainty, enjoy working collaboratively on challenging problems, and celebrate one another’s victories.

We go above and beyond, but also strive to provide a supportive atmosphere of colleagues who are willing to lend a helping hand and make working at Nautilus not only fulfilling in its end goals, but enjoyable on a day-to-day basis.

Our Values:

Be Excellent

Be a Good Human

Catalyze Customer Success

Dream Big

Drive for Results

Enjoy the Voyage

Succeed as One Team