This Stealth Mode Company is a top-tier venture backed, privately held biotechnology company on a mission to create "a new modality to end all modalities". The team is aspiring to drastically scale up and change the trajectory of drug discovery by tackling the biggest challenges of existing modalities, and applying the platform to targets with the highest impact for patients. The Company is being co-founded by a seasoned entrepreneur with a track record of establishing successful biotech ventures, both public and private, alongside another co-founder who formerly served as President of R&D for a large pharmaceutical company.
Overview
We are seeking a highly motivated Senior Machine Learning Scientist to join our growing company. The ideal candidate will have hands-on experience in a drug discovery setting with machine learning for molecules (either small molecules or larger biomolecules) using both established cheminformatic representations/models and newer deep learning approaches.
This role is located in Cambridge/Watertown, MA.
Job Responsibilities
- Build data processing and curation pipelines for experimental data.
- Design, build, train, and evaluate machine learning models on molecules for a variety of properties, including binding affinity and pharmacokinetic properties. These models include well established models like Random Forests, Support Vector Machines, or Gaussian Process using fingerprint representations as well as neural network models such as graph convolutional neural networks and transformer-based language models.
- Use trained models for virtual screening and/or generative models to select promising molecules for our programs.
- Stay abreast of emerging research in machine learning for molecules.
- Collaborate closely with experimental scientists and other stakeholders to deliver effective models and predictions.
Job Requirements
- B.S. in computer science with 5+ years of industry experience or Ph.D. in computer science, chemoinformatics, mathematics, or related discipline with a minimum of 2 years of industry or post-doctoral academic experience in pharma / biotech with machine learning on either small molecules or larger biomolecules.
- Skilled in Python programming.
- Hands on experience with at least one cheminformatics software package such as RDKit or OpenEye.
- Experience in deep learning model development in Python and relevant ML libraries: (e.g. TensorFlow, PyTorch).
- Excellent communication and interpersonal skills.
- Strong analytical and critical thinking skills, both scientifically and in the ability to prioritize tasks, set deadlines, and adapt to shifting priorities.
- Ideal candidates will also have experience with molecular representational issues such as tautomerization and protonation, generative models, and molecular visualization tools such as PyMOL or VMD.