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. The Role We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into pretraining large-scale deep learning models for biomolecular design. This position offers an opportunity to work at the forefront of generative modeling research across language processing, representation learning, and protein engineering. You should be a self-directed researcher who has the ability to rapidly prototype and evaluate new models and algorithms in the biomolecular domain. As an early employee, you will proactively shape the direction of our machine learning efforts and collaborate across diverse teams of computational and experimental scientists. Responsibilities Design and develop state-of-the-art autoregressive, diffusion and representation learning models for protein design Collaborate across the machine learning and protein design teams to apply, adapt and improve pretraining techniques from other domains to biomolecular deep learning models Architect, implement, and optimize core infrastructure to support the pretraining of protein language models Curate relevant datasets and design tasks for rigorous evaluation of generative models 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 Qualifications 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 and pretraining large scale LLMs or other models in biomolecular domain Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS) or experience pre-training LLMs at frontier AI/ML labs Experience with modern deep learning frameworks such as Pytorch or Jax Preferences Familiarity with foundational biology of proteins and nucleic acids Experience developing machine learning models for proteins (language models, structure prediction, design) Experience with cloud compute platforms (GCP, AWS, Azure, OCI) Previous experience in data extraction and curation from bioinformatics data sources Familiarity with wet lab experimental assays and associated limitations 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.

Requirements

Must-haves

As an early employee, you will proactively shape the direction of our machine learning efforts and collaborate across diverse teams of computational and experimental scientists.
Design and develop state-of-the-art autoregressive, diffusion and representation learning models for protein design
Collaborate across the machine learning and protein design teams to apply, adapt and improve pretraining techniques from other domains to biomolecular deep learning models
Architect, implement, and optimize core infrastructure to support the pretraining of protein language models
Curate relevant datasets and design tasks for rigorous evaluation of generative models
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
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 and pretraining large scale LLMs or other models in biomolecular domain
Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS) or experience pre-training LLMs at frontier AI/ML labs
Experience with modern deep learning frameworks such as Pytorch or Jax
Familiarity with foundational biology of proteins and nucleic acids
Experience developing machine learning models for proteins (language models, structure prediction, design)
Experience with cloud compute platforms (GCP, AWS, Azure, OCI)
Previous experience in data extraction and curation from bioinformatics data sources
Familiarity with wet lab experimental assays and associated limitations

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aimachine learningmlgcpawsazure

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Professional Development