As one of my client’s early ML team members, you’ll play a foundational role in shaping our technology and scientific direction. They are an AI-driven biotechnology company designing programmable protein therapeutics to tackle the world’s most challenging diseases. Founded by leading AI pioneers and backed by top-tier investors. You’ll lead transformational research in close collaboration with a multidisciplinary team of AI researchers, protein engineers, and drug discovery experts.

You will:

Develop next-generation generative protein design pipelines, from novel architectures to computational candidate submission for wet-lab testing.
Build closed-loop training systems integrated with high-throughput experimental workflows.
Rapidly prototype, evaluate, and iterate on new models and algorithms with autonomy and creativity.
Contribute directly to the design of novel proteins with the potential to transform human health.

Qualifications

Required:

Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology, or a related quantitative field and 2+ years relevant industry experience, or equivalent industry experience in ML.
Experience developing LLMs, diffusion models, or flow-matching generative models.
Strong proficiency in Python and modern deep-learning frameworks.
Ability to translate open-ended scientific challenges into tractable modeling objectives and to communicate them clearly across teams.

Preferred:

Experience with generative models for protein folding or design.
Peer-reviewed ML publications or meaningful contributions to open-source ML libraries.

What We Offer

The opportunity to pioneer at the frontier of AI for science.
A chance to help develop the next generation of life-changing therapeutics.
A high-agency startup environment with seasoned leadership and advisors, including a two-time founder and the former CEO of one of the world’s largest pharmaceutical companies.

If you’re excited to push the boundaries of machine learning and help build the future of programmable medicine, we’d love to hear from you.

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