Protein Design Scientist – Agentic Workflows

Profluent Bio

. Design, build, and deploy end-to-end agentic workflows that take protein function specifications and produce ranked candidate sequences for experimental validation .

Posted 4/24/2026full-timeEmeryville • California • 🇺🇸 United StatesMid-LevelSenior💰 $180,000 - $250,000 per yearWebsite

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design, build, and deploy end-to-end agentic workflows that take protein function specifications and produce ranked candidate sequences for experimental validation
Integrate protein language models, structure prediction tools, and scoring functions into multi-step pipelines with iteration, feedback loops, and human-in-the-loop checkpoints
Own the full lifecycle of workflow systems: architecture, implementation, testing, deployment, monitoring, and iteration based on experimental outcomes
Collaborate with ML scientists to evaluate and integrate new models into workflows, and with protein design scientists and biologists to translate scientific goals into computational specifications and ensure workflows align with experimental realities
Develop tooling for experiment tracking, logging, reproducibility, and versioning of design campaigns
Evaluate and benchmark workflow performance against experimental results, using outcomes to improve agent strategies and model selection
Partner with ML scientists to identify where existing models fall short in agentic contexts and inform priorities for model development, fine-tuning, and evaluation

Requirements

What you’ll need

PhD (or equivalent industry experience) in Computational Biology, Bioinformatics, Computer Science, Machine Learning, Biochemistry, or a related field
Strong software engineering skills: you write clean, modular, production-quality code (Python required; experience with workflow orchestration frameworks is a plus)
Hands-on experience with protein language models (e.g., ESM, ProGen, ProtTrans) for sequence generation, scoring, or representation
Demonstrated understanding of protein engineering principles: structure-function relationships, fitness landscapes, and how computational predictions connect to wet-lab validation
Experience building multi-component systems that chain model inference with data processing, filtering, and decision logic

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

Pythonworkflow orchestration frameworksprotein language modelsESMProGenProtTranssoftware engineeringclean codemodular codeproduction-quality code

Soft Skills

collaborationcommunicationproblem-solvingiterationfeedback loopsadaptabilityorganizational skillsattention to detailcritical thinkingtranslating scientific goals

Certifications

PhD in Computational BiologyPhD in BioinformaticsPhD in Computer SciencePhD in Machine LearningPhD in Biochemistry