Machine Learning Scientist, BioML

Profluent Bio

Machine Learning Scientist driving AI research for protein design at Profluent. Working on generative modeling in a collaborative team environment for biomedicine.

Posted 6/5/2026full-timeEmeryville • California • 🇺🇸 United StatesMid-LevelSenior💰 $200,000 - $330,000 per yearWebsite

ATS Keywords

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Hard Skills

machine learningpredictive modelsgenerative modelsdeep learningcomputational approachesdata analysismodel evaluationnatural language processingcomputational biologystatistics

Soft Skills

collaborationcommunicationinterdisciplinary teamworkpresentation skillsproblem-solvingadaptabilitystrategic vision

Tools & Technologies

PytorchJaxdata curationexperimental validationdatasetscomputational tools

Certifications & Qualifications

PhD in Computer SciencePhD in Machine LearningPhD in Natural Language ProcessingPhD in Applied MathPhD in Computational BiologyPhD in Statistics

Industry Keywords

protein designnucleic acid dataevolutionary datamachine learning conferencesNeurIPSICMLICLRscientific journalsNatureScience

Tech Stack

Tools & technologies

PyTorch

About the role

Key responsibilities & impact

Design and develop state-of-the-art predictive and generative models incorporating domain-specific evolutionary and experimental data
Leverage massive-scale protein and nucleic acid data to train specialized models for protein understanding and design
Curate relevant datasets and design tasks for rigorous evaluation of generative models
Collaborate across the machine learning and protein design teams to adapt and apply techniques for experimental validation
Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings
Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company

Requirements

What you’ll need

PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field
Experience with conceiving of, implementing, and evaluating novel machine learning techniques at the intersection with biology
Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS)
Experience with modern deep learning frameworks such as Pytorch or Jax

Benefits

Comp & perks

High-growth opportunity with meaningful impact on the future of protein design
Competitive compensation package with equity participation
401(k) with a strong employer match
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