Machine Learning Scientist, Biomolecular Structure Prediction

Profluent
Location
Emeryville, California, United States
Job Type
Full-time
Posted
November 5, 2026

Job Description

Profluent is the frontier AI lab for biology. Profluent builds powerful foundation models for all of life's molecules, unlocking solutions that transform medicine, agriculture, and beyond. Founded in 2022 and headquartered in Emeryville, CA, Profluent is backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures and has raised over $150M to date.

We're looking for a motivated and creativeMachine Learning (ML) Scientistto drive research into biomolecular structure prediction. You will build and improve all-atom co-folding models, with a focus on the complexes that matter most to our programs: antibody–antigen interfaces and protein–nucleic acid assemblies. These remain among the hardest cases for current models, and closing that gap directly accelerates our antibody design and genome editing work.

The ideal candidate has trained structure prediction models at a leading academic or industry lab and knows where today's models break. You will be a self-directed researcher who moves quickly from hypothesis to trained model to rigorous evaluation. As an early member of the ML team, you will help shape how structure modeling fits alongside our generative models (ProGen3, E1) and experimental platforms.

Responsibilities

  • Develop and train all-atom structure prediction models, improving accuracy on antibody–antigen and protein–nucleic acid complexes
  • Diagnose failure modes of current models (e.g., CDR-H3 and epitope placement, interface geometry, nucleic acid conformations, confidence calibration) and design architecture, training, and data interventions to address them
  • Curate large-scale training data from structural databases, distillation sets, and Profluent's own experimental binding and function data
  • Integrate structure models with our generative models for design and filtering, and work with protein design teams on experimental validation
  • Present results to colleagues in regular update meetings

Qualifications

  • PhD (or equivalent industry experience) in computer science, computational biology, biophysics, or a related field
  • Hands-on experience building and training biomolecular structure prediction models (e.g., AlphaFold- or Protenix-style co-folding models) at a leading academic or industry lab
  • Publications at major ML conferences (NeurIPS, ICML, ICLR) or top science journals, or widely used open-source models
  • Experience with deep learning frameworks such as PyTorch or JAX, including multi-GPU training

Preferences

  • Experience modeling antibody structure and antibody–antigen docking, including CDR loop modeling and epitope prediction
  • Experience modeling protein–DNA or protein–RNA complexes
  • Deep familiarity with structural data pipelines: mmCIF processing, MSA and template search, structural clustering, and dataset splitting
  • Experience with diffusion or flow-matching models for structure generation or structure-conditioned design
  • Experience with large-scale distributed training and cloud compute
  • Familiarity with experimental structural and binding data (cryo-EM, crystallography, display-based binding assays)

What We Offer

  • 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

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Profluent is the frontier AI lab for biology. Profluent builds powerful foundation models for all of life's molecules, unlocking solutions that transform medicine, agriculture, and beyond. Founded in 2022 and headquartered in Emeryville, CA, Profluent is backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures and has raised over $150M to date.

We're looking for a motivated and creativeMachine Learning (ML) Scientistto drive research into biomolecular structure prediction. You will build and improve all-atom co-folding models, with a focus on the complexes that matter most to our programs: antibody–antigen interfaces and protein–nucleic acid assemblies. These remain among the hardest cases for current models, and closing that gap directly accelerates our antibody design and genome editing work.

The ideal candidate has trained structure prediction models at a leading academic or industry lab and knows where today's models break. You will be a self-directed researcher who moves quickly from hypothesis to trained model to rigorous evaluation. As an early member of the ML team, you will help shape how structure modeling fits alongside our generative models (ProGen3, E1) and experimental platforms.

Responsibilities

  • Develop and train all-atom structure prediction models, improving accuracy on antibody–antigen and protein–nucleic acid complexes
  • Diagnose failure modes of current models (e.g., CDR-H3 and epitope placement, interface geometry, nucleic acid conformations, confidence calibration) and design architecture, training, and data interventions to address them
  • Curate large-scale training data from structural databases, distillation sets, and Profluent's own experimental binding and function data
  • Integrate structure models with our generative models for design and filtering, and work with protein design teams on experimental validation
  • Present results to colleagues in regular update meetings

Qualifications

  • PhD (or equivalent industry experience) in computer science, computational biology, biophysics, or a related field
  • Hands-on experience building and training biomolecular structure prediction models (e.g., AlphaFold- or Protenix-style co-folding models) at a leading academic or industry lab
  • Publications at major ML conferences (NeurIPS, ICML, ICLR) or top science journals, or widely used open-source models
  • Experience with deep learning frameworks such as PyTorch or JAX, including multi-GPU training

Preferences

  • Experience modeling antibody structure and antibody–antigen docking, including CDR loop modeling and epitope prediction
  • Experience modeling protein–DNA or protein–RNA complexes
  • Deep familiarity with structural data pipelines: mmCIF processing, MSA and template search, structural clustering, and dataset splitting
  • Experience with diffusion or flow-matching models for structure generation or structure-conditioned design
  • Experience with large-scale distributed training and cloud compute
  • Familiarity with experimental structural and binding data (cryo-EM, crystallography, display-based binding assays)

What We Offer

  • 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

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

Hiring Salary Range

$212,000—$339,000 USD

NOTICE TO STAFFING AND SEARCH FIRMS:Profluent does not accept unsolicited candidate submissions. We ask that agencies refrain from sending resumes to our careers inbox, hiring managers, or any Profluent employee. Any resume submitted without a signed agreement and an active search request from our Talent team will be treated as the property of Profluent, and no placement fee will be owed.

Frequently Asked Questions

Where is this role located?
The job is located in Emeryville, California, United States. The posting does not specify a remote, hybrid, or on-site work-mode policy.
What qualifications are required for this position?
Candidates must have a PhD (or equivalent industry experience) in computer science, computational biology, biophysics, or a related field; hands-on experience building/training biomolecular structure prediction models; top-tier conference publications, journal papers, or open-source models; and PyTorch or JAX experience with multi-GPU training.
What are the primary responsibilities of a Machine Learning Scientist in this role?
You will develop, train, and improve all-atom structure prediction models, diagnose model failure modes, curate large-scale training data, integrate structure models with generative models, collaborate with protein design teams on experimental validation, and present results in regular update meetings.
What is the compensation range for this job?
The hiring salary range for this position is $212,000 to $339,000 USD.
Does Profluent offer visa sponsorship for this position?
Legal authorization to work in the United States is required. Hired employees must verify their identity and work eligibility upon hire. The posting does not mention offering visa sponsorship or relocation support.
What benefits does Profluent offer?
Profluent offers a competitive compensation package with equity, a 401(k) with employer match, health/dental/vision insurance, a generous PTO policy, and professional development opportunities.

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Job Information

Source: greenhouse
AI Relevance: 95/100 (Highly relevant)
Remote Type: onsite
Skills & Tags:
Machine Learning
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