Scientist II, ML – Guided Protein Design Evaluation

Profluent Bio

Scientist II specializing in ML-guided protein design at Profluent. Collaborating on therapeutic antibody development and ensuring data quality for improvement of protein design models.

Posted 6/24/2026full-timeEmeryville • California • 🇺🇸 United StatesMid-LevelSenior💰 $147,000 - $180,000 per yearWebsite

About the role

Key responsibilities & impact

Partner with ML and Protein Design leads to scope MDE campaigns; including target selection, choice of assays, and what readouts are needed to improve the next generation of models
Define assay readiness levels, controls, and QC acceptance criteria for each campaign, and enforce them across internal execution and external CROs
Review incoming data (biochemical, biophysical, NGS-based screens) for scientific soundness before it is accepted into the data warehouse and used for model training
Work with Bioinformatics on metadata schemas and data ingestion so that every dataset is consistent, queryable, and traceable back to its parent project.
Serve as the scientific point of contact for CRO technical scoping; evaluate whether a vendor’s platform, assay conditions, and controls are fit for purpose for ML-guided optimization
Contribute to campaign charters, benchmarking assay design, and post-campaign readouts; help turn individual experiments into a growing institutional dataset
Represent the MDE program in cross-functional technical forums and help raise the data-quality bar across the organization

Requirements

What you’ll need

PhD in Molecular Biology, Biochemistry, Protein Engineering, Biophysics, Immunology, or a closely related field; or MS with equivalent industry experience
5+ years of hands-on experience with protein engineering and functional characterization, including biochemical activity, binding, stability, and/or expression assays
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
Demonstrated ability to define assay quality standards (signal/noise, reproducibility, plate-level controls) and hold experimental workflows to them
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.

Benefits

Comp & perks

Competitive compensation package with equity participation
Comprehensive benefits including health/dental/vision insurance
Generous PTO policy and commitment to work-life balance
Professional development opportunities in a cutting-edge field at the intersection of AI and biology

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

protein engineeringfunctional characterizationbiochemical activity assaysbinding assaysstability assaysexpression assaystherapeutic antibody discoveryaffinity maturationNGS-based screening workflowsassay quality standards

Soft Skills

cross-functional collaborationcommunicationscientific soundness evaluationdata quality assuranceinterdisciplinary fluency

Certifications

PhD in Molecular BiologyPhD in BiochemistryPhD in Protein EngineeringPhD in BiophysicsPhD in ImmunologyMS in related field