Senior Scientist, Machine Learning

About Generate : Biomedicines

Make sure to apply with all the requested information, as laid out in the job overview below.

Generate : Biomedicines is a new kind of therapeutics company existing at the intersection of machine learning, biological engineering, and medicine pioneering Generative Biology to create breakthrough medicines where novel therapeutics are computationally generated, instead of being discovered.

The Company has built a machine learning-powered biomedicines platform with the potential to generate new drugs across a wide range of biologic modalities.

This platform represents a potentially fundamental shift in what is possible in the field of biotherapeutic development.

We pursue this audacious vision because we believe in the unique and revolutionary power of generative biology to radically transform the lives of billions, with an outsized opportunity for patients in need.

We are seeking collaborative, relentless problem solvers that share our passion for impact to join us!

Generate : Biomedicines was founded in 2018 by Flagship Pioneering and has received nearly $700 million in funding, providing the resources to rapidly scale the organization.

The Company has offices in Somerville and Andover, Massachusetts with over 300 employees.

The Role :

The machine learning team at Generate creates new generative models and algorithms that drive the production of novel proteins at scale.

We leverage foundational knowledge of generative modeling, protein biophysics, and biology to develop frontier systems and collaborate broadly with our computational and wet lab teams to deploy them for creating new therapeutics.

Some of our work is illustrated in our recent publication of Chroma in Nature.

We are seeking creative, motivated, and rigorous Machine Learning Scientists to develop our core generative technologies for ML-powered protein design.

They will join a vibrant ML group that is creating novel methods and collaborate broadly with our wet and dry lab scientists to maximally leverage both in-house and external data.

They will work with our engineering teams to scale model training and build new state-of-the-art protein design applications that will define the future of biotherapeutics.

Here's How You Will Contribute :

• Develop foundational generative models and algorithms for designing and reasoning about the sequences, structures, and functions of proteins.
• Scale systems with our extensive GPU resources to maximally leverage protein and biological data, combining all that can be learned from evolution, the scientific literature, and active data acquisition in our proprietary, in-house high throughput assays and Cryo-EM platform.
• Collaborate with wet lab and platform technology teams to unlock high-impact therapeutic applications and design novel proteins across diverse therapeutic modalities.
• Engineer production-grade machine learning systems in conjunction with our Engineering teams for large-scale distributed compute setups and be deployed for design of million-variant+ de novo libraries.
• Present in regular research meetings and prepare materials for broader internal and external communication across disciplines.
• See your generative models produce real proteins that are built, characterized, and on a path to be life-changing therapies.

The Ideal Candidate Will Have :

• PhD in Computational Biology, Computer Science, or a related field with a track record of innovative ML method development for scientific applications.
• Experience developing ML methods to solve scientific problems, with a particular interest towards applications to protein modeling as well as adjacent fields such as genomics, chemistry, immunology, or physics.
• Experience developing, debugging, and scaling models using modern deep learning frameworks such as Pytorch or JAX.
• Proficiency in Python and experience analyzing data with Numpy / Scipy, R, or similar.

Nice to have :

• Foundational knowledge of probabilistic ML and inference methods.
• Practical experience with developing deep generative models (e.g., language models, diffusion models, EBMs, VAEs, flows, etc.).
• Domain expertise around protein design, biochemistry, genetics, biophysics, and / or chemistry as well as practical experience working with data in these domains.
• Publications at major scientific venues such as ML conferences or scientific journals that apply ML to advance problems in molecular biology, structural biology, or genetics, especially at the intersection of ML and proteins.
• Demonstrated experience developing software in a team setting.
• Experience with optimizing performant code.

COVID Safety :

Generate : Biomedicines enforces a mandatory vaccination policy for COVID-19. All employees must be fully vaccinated and have received a booster.

The purpose of this policy is to safeguard the health of our employees, their families, and the community at large from infectious disease that may be reduced by vaccinations.

The Company will make exceptions to this policy if required by applicable law and will consider requests for an exemption from this policy due to a medical reason, or because of a sincerely held religious belief, or any other exemptions that may be recognized by applicable.

Equal Opportunity Employment :

Generate : Biomedicines is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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