CHARM Therapeutics is a new biotech company focused on delivering transformational medicines to patients through the application of 3-D deep learning on molecular configurations.
Along with scalable cloud computing, modern drug discovery technologies and a culture that allows for creative risk-taking, we intend to develop drugs against historically difficult-to-drug targets involved in key oncogenic pathways.
CHARM Therapeutics seeks a mission-driven machine learning engineer to help us research and develop cutting-edge methods of 3D deep learning and apply them to drug discovery.
The Role
- Building and training of sophisticated transformers operating on molecular graphs.
- Processing of datasets to feed into these models.
- Application of these models to different drug discovery tasks.
- Surveying and keeping up-to-date with the relevant literature to see if it can be integrated into our projects.
Requirements
- BS/MS in computer science, mathematics, physics, chemistry or related field from a top institution.
- 1-3+ years of experience in a MLE role at a tech or biotech company.
- Experience training transformer architectures.
- Experience training deep nets on multiple GPUs.
- Excellent interpersonal skills, oral and written communication skills. Willing to genuinely work within an interdisciplinary team and learn the domains of other fields.
- Comfortable in Pytorch and/or JAX.
Nice-to-haves
- PhD in machine learning, chemistry, structural biology or related field.
- Previously applied machine learning to chemistry or structural biology.
- Experience with bio and chem toolkits (e.g RDKit, Openeye, BioPython, etc)
- Savvy in state-of-the-art deep learning techniques (gradient rematerialization etc).
- ML Ops tools (Pytorch Lightning, onnx, jit, deepspeed).
- Understanding of equivariance and representation theory.
