Dreamfold
About Us
Dreamfold’s mission is to design programmable protein therapeutics for the world’s most challenging diseases, from cancer and immune disorders to infectious diseases and beyond. Founded in the labs of AI pioneers Yoshua Bengio and Michael Bronstein, Dreamfold is backed by Midas List investors, as well as early engineers and executives from Meta and Google. We’re seeking deeply self-motivated leaders to push the boundaries of what machine learning can achieve in human health. This is a chance not just to build cutting‑edge AI models, but to create life‑changing medicine. About the Role
As a Machine Learning Scientist and one of Dreamfold’s early team members, you will play a foundational role in shaping our technology. You will lead transformational ML research in close collaboration with our growing team of AI and drug discovery scientists, engineers, and world‑class advisors. In this role, you will:
Drive the development of generative protein design pipelines, from designing novel model architectures to evaluating and submitting computational designs for wet‑lab testing.
Build closed‑loop training paradigms tightly integrated with high‑throughput experimental workflows, enabling iterative hypothesis generation grounded in real‑world, disease‑relevant biology.
Take ownership of core ML components, rapidly prototyping and evaluating new models and algorithms with autonomy, creativity, and critical thinking.
Contribute directly to the creation of novel proteins with the potential to transform human health.
About You
You’re driven to solve high‑impact technical and scientific challenges that make a real difference in human health. Your curiosity and desire to understand core problems across ML, protein design, and drug discovery fuel your success in collaborative, cross‑disciplinary teams, while keeping you resilient, adaptable, and solution‑focused in fast‑moving, dynamic environments. Your Experience
Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology, or a related quantitative field,
and
2 years of relevant industry experience,
OR
equivalent industry experience in machine learning.
Demonstrated experience developing LLMs, diffusion models, or flow‑matching–based generative models.
Strong proficiency in Python and modern deep‑learning frameworks.
Proven ability to navigate open‑ended, multi‑disciplinary problems, translate them into tractable modelling objectives, and communicate complex technical concepts across teams.
Preferred experience
Prior work on generative models for protein folding and/or design.
Peer‑reviewed publications in ML and/or meaningful contributions to open‑source ML libraries.
Our Commitments to You
Pioneering work at the frontier of AI for science.
The opportunity to help create the next generation of life‑changing medicine.
A fast‑moving, high‑agency startup environment with a deeply technical team, seasoned leadership, and world‑class scientific and business minds, including a successful two‑time founder and the former CEO of one of the world’s largest pharmaceutical companies.
Competitive compensation, including a meaningful ownership stake.
Comprehensive health insurance, including vision, dental, and prescription coverage.
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Dreamfold’s mission is to design programmable protein therapeutics for the world’s most challenging diseases, from cancer and immune disorders to infectious diseases and beyond. Founded in the labs of AI pioneers Yoshua Bengio and Michael Bronstein, Dreamfold is backed by Midas List investors, as well as early engineers and executives from Meta and Google. We’re seeking deeply self-motivated leaders to push the boundaries of what machine learning can achieve in human health. This is a chance not just to build cutting‑edge AI models, but to create life‑changing medicine. About the Role
As a Machine Learning Scientist and one of Dreamfold’s early team members, you will play a foundational role in shaping our technology. You will lead transformational ML research in close collaboration with our growing team of AI and drug discovery scientists, engineers, and world‑class advisors. In this role, you will:
Drive the development of generative protein design pipelines, from designing novel model architectures to evaluating and submitting computational designs for wet‑lab testing.
Build closed‑loop training paradigms tightly integrated with high‑throughput experimental workflows, enabling iterative hypothesis generation grounded in real‑world, disease‑relevant biology.
Take ownership of core ML components, rapidly prototyping and evaluating new models and algorithms with autonomy, creativity, and critical thinking.
Contribute directly to the creation of novel proteins with the potential to transform human health.
About You
You’re driven to solve high‑impact technical and scientific challenges that make a real difference in human health. Your curiosity and desire to understand core problems across ML, protein design, and drug discovery fuel your success in collaborative, cross‑disciplinary teams, while keeping you resilient, adaptable, and solution‑focused in fast‑moving, dynamic environments. Your Experience
Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology, or a related quantitative field,
and
2 years of relevant industry experience,
OR
equivalent industry experience in machine learning.
Demonstrated experience developing LLMs, diffusion models, or flow‑matching–based generative models.
Strong proficiency in Python and modern deep‑learning frameworks.
Proven ability to navigate open‑ended, multi‑disciplinary problems, translate them into tractable modelling objectives, and communicate complex technical concepts across teams.
Preferred experience
Prior work on generative models for protein folding and/or design.
Peer‑reviewed publications in ML and/or meaningful contributions to open‑source ML libraries.
Our Commitments to You
Pioneering work at the frontier of AI for science.
The opportunity to help create the next generation of life‑changing medicine.
A fast‑moving, high‑agency startup environment with a deeply technical team, seasoned leadership, and world‑class scientific and business minds, including a successful two‑time founder and the former CEO of one of the world’s largest pharmaceutical companies.
Competitive compensation, including a meaningful ownership stake.
Comprehensive health insurance, including vision, dental, and prescription coverage.
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