Job Description

Machine Learning Engineer / Computational Biologist Protein Design

1910 Genetics is the only company that has built a synergistic, dual-purpose small and large molecule platform that integrates artificial intelligence (AI), computation, and biological automation to design drug-like molecules better, faster, and cheaper than traditional approaches. Based in the Seaport District of Boston, 1910 Genetics is a Series A stage biotechnology startup that was founded in 2018 and is backed by prestigious investors, including M12-Microsofts Venture Fund, Sam Altman the CEO of OpenAI (makers of ChatGPT), Playground Global, Y Combinator, New Ventures Funds (Scientia Ventures), and many others.

At 1910 Genetics, we first established an understanding of the molecular basis of disease to the granularity at which the world understands sickle cell anemia. This understanding centers biology as our North Star and drives our integration of artificial intelligence (AI), computation, and biological automation to accelerate the design of small molecule and protein therapeutics.

Recent advances in computational technologies have placed historically undruggable targets within therapeutic reach. But at 1910 Genetics, we often say Biology is King, meaning that computational technologies are only impactful in drug discovery when driven by experimental biology. Our platforms scale and breadth empower us to be therapeutic area-agnostic with programs ranging from neuroscience and immunology to infectious disease and oncology, to name a few.

We are looking for a rock star to join our team as a Machine Learning Engineer focused on protein design. To be effective in this role, you will need to be exceptional in structural biology, biophysics, and machine learning engineering.

We can count on you to

• Work closely with our academic Founding Scientist to build and launch our protein design platform with several applications including but not limited to protein structure refinement, protein structure prediction, therapeutic protein design, among other basic and translational research applications.

You will own

• All aspects of 1910s protein design platform.

You will teach

• Your cross-disciplinary colleagues from Computational Chemistry, Medicinal Chemistry, Computational Biology, Cell Biology, and Pharmacology how the protein design platform can be applied in their structure-based design of small molecule therapeutics.

You will learn...

• Drug discovery and development.

You will improve

• The pace of development of 1910s protein design platform.

Within 1 month you will

• Understand the core scientific principles of structural biology, biochemistry, and biophysics that underlie 1910s protein design platform.
• Understand our proprietary dataset of rich amino acid data that powers the protein design platform.
• Form a view on which AI/ML models best address different applications of the protein design platform.

Within 3 months you will

• Complete preliminary testing of possible database structures, scoring functions, and machine learning algorithms for the protein design platform.
• Productionize the best algorithms on AWS.

Within 6 months you will

• Launch the beta product of the protein structure refinement module.

Within 1 year you will

• Launch the full protein structure refinement module.
• Launch the protein structure prediction module.
• Begin prototyping the therapeutic protein design module.

Extremely generous equity package coupled with competitive salary.

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