Scientist, Machine Learning
- Design and implement novel transformer-based machine learning architectures to push forward our drug design programs.
- Collaborate with our laboratory scientists to build models that most effectively inform our internal stakeholders of key insights into mechanisms of RNA biology.
- Collaborate with our IT and Engineering teams to effectively deploy ML solutions to the organization at large.
- Design and implement methodologies allowing for improved usage and comprehension of complex models by internal stakeholders.
- PhD with 0-3 years of experience, or MS with 5+ years of experience in artificial intelligence, computer science, computational biology, computational chemistry, bioinformatics, or a related field.
- Familiarity with structural biology/chemistry (of DNA, RNA and/or proteins)
- Knowledge of the drug development process.
- Expert knowledge of SOTA transformer architectures, including but not limited to T5, BERT, GPT, PaLM2, etc.
- Experience training large models at scale, including distributed training strategies.
- Established experience in machine learning algorithm development and innovation, in industry or academia, with a proven track record of independent research.
- Strong background in ML Framework libraries, including at least one deep learning framework (e.g., PyTorch, Tensorflow, JAX, etc.).
- Working knowledge of the model lifecycle process and an MLOps platform (e.g., Databricks, Sagemaker, AzureML, etc.).
- Outstanding oral and written communication skills.
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