Profluent
Scientist II, ML - Guided Protein Design Evaluation
Emeryville, California, United States; Hybrid (2-3 days on-site) · Mid
Work authorization required$147k-$180kDetected 28 days ago
PythonSQLMachine LearningPandasSparkBioinformaticsCRISPRMolecular BiologyNGSPublic Speaking
About the role
- This is a hands-on technical role, not a pure program role.
Responsibilities
- Partner with ML and Protein Design leads to scope MDE campaigns
- Contribute to campaign charters, benchmarking assay design, and post-campaign readouts
Requirements
- 5+ years of hands-on experience with protein engineering and functional characterization, including biochemical activity, binding, stability, and/or expression assays
- Demonstrated ability to define assay quality standards (signal/noise, reproducibility, plate-level controls) and hold experimental workflows to them
- Experience with display-based antibody discovery platforms (phage, yeast, mammalian) and/or single-cell B-cell screening workflows
- Experience scoping and overseeing externally run assays at CROs, including technical evaluation of vendor platforms
- Familiarity with LIMS and project-management systems and experience defining data & metadata schemas for experimental data
- PhD in Molecular Biology, Biochemistry, Protein Engineering, Biophysics, Immunology, or a closely related field; or MS with equivalent industry experience
- Direct experience with therapeutic antibody discovery and engineering (e.g., affinity maturation, developability optimization, humanization, format engineering) and the assays that support it (binding kinetics, epitope characterization, biophysical and developability panels)
- Strong working knowledge of NGS-based screening workflows (e.g., deep mutational scanning, amplicon sequencing, high-throughput activity screens, antibody display library sequencing) and what makes that data usable for modeling
- Fluent working across scientific disciplines; can talk protein chemistry and antibody biology with biologists and model-guided design approaches with ML scientists without losing either audience
- Prior experience closing Design-Build-Test-Learn loops in an industrial protein design, antibody engineering, or directed evolution setting
- Comfortable with Python/pandas and SQL at the level needed to inspect, QC, and reason about experimental datasets independently
- Track record of publishing, presenting, or shipping work at the intersection of protein engineering and machine learning
- High-growth opportunity with meaningful impact on the future of protein design
Nice to have
- Exposure to kinases, nucleases, recombinases, or gene editing enzymes is a plus
Compensation
- Competitive compensation package with equity participation
Benefits
- Competitive compensation package with equity participation
- Comprehensive benefits including health/dental/vision insurance
- Generous PTO policy and commitment to work-life balance
Equal opportunity
- equal opportunity employer promoting diversity and inclusion in the workspace.
Visa & Work Authorization
- Applicants must have ongoing work authorization in the United States that does not require employer sponsorship.
- Sponsorship will not be provided now or at any time in the future for this position.
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