Work with a cross functional team of scientists and engineers building foundational models that are used, tested, and trained on real world applications of generative design to the development of therapeutic biomolecules.
Develop and implement groundbreaking machine learning and protein science solutions.
Collaborate with computational and experimental scientists to establish these tools as a foundation of the discovery pipeline.
Work towards individual ownership and a leadership role in determining model architectures and research program needs.
Engage with open source and academic collaborations in the machine learning field.

Doctorate degree OR Master’s degree and 2 years of machine learning experience OR Bachelor’s degree and 4 years of machine learning experience OR Associate’s degree and 8 years of machine learning experience
PhD in in Computational Sciences, Computational Biology, Applied Math, Statistics or related quantitative field.
Strong track record of research accomplishments including three or more scientific publications or conference presentations in machine learning
Experience specifically with model training and diffusion model architecture, demonstrated by scientific publication or conference presentations.
Experience with UNIX/Linux, Python, PyTorch, Git, and cloud computing platforms
Experience working with biological data, and in applying machine learning to computational biology
Strong communication and technical leadership skills with an enthusiasm for working in an interdisciplinary team environment.

A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions
group medical, dental and vision coverage
life and disability insurance
flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible.

Machine Learning Scientist

Key skills