I’m working with a next-generation AI-driven biotech company (~20 people) based in NYC to find a Senior Machine Learning Scientist (flexible to Director title) to join their team. They have been able to develop a high-performance computing framework to conduct large-scale MD studies combined with AI-augmented free-energy-based methods – all in order to initiate and accelerate preclinical drug discovery against emerging and challenging drug target classes.
You will be working closely alongside their team of medicinal chemists, infrastructure engineers, molecular biologists, biophysicists, and theoretical physicists while reporting to the VP, Machine Learning. This will give you the opportunity to balance work on research projects with pressing demand for optimized models across therapeutic developments as well as to work on longer-term projects.
You would be expected to:
Develop ML / statistical models for predicting molecular properties ranging from low-data to big-data regimes.
Develop generative models for optimal models.
Integrate individual models within the bigger picture of ML and physics modules used internally.
Design benchmarking tools and test datasets.
Work closely with the infrastructure team to build production-level tools and integrate with the internal pipeline.
They are looking for someone who possesses the following:
Ph.D. in Computer Science, Statistics, Machine Learning, or a related field with a heavy machine learning emphasis.
3+ years of industry experience conducing ML research (biopharma/drug discovery environment preferred).
Very strong and proven ability to implement powerful ML libraries or code.
Experience building transformer models or generative models.
If you are interested in the above role and think you would be a good fit, please apply or reach out to me directly at email@example.com.