At Reverie Labs, we’re building a pharmaceutical company from the ground up using computation—we’re a drug company that looks and feels like a tech company. We’re a team of engineers and machine learning researchers using cutting-edge tools to design new medicines.

Here’s a small sample of some of the hard tasks we solve to accomplish our goal of developing life-saving treatments for patients:

• Developing new machine learning algorithms and architectures to model complex biological systems. 
• Translating state-of-the-art machine learning techniques designed to work on images, text, or audio into the domain of molecules. 
• Creating a large-scale distributed training and hyperparameter optimization system. 
• Using data mining and processing techniques to uncover new sources of data and clean our existing datasets. 
• Using predictive modeling to make critical decisions about which tests to run in the lab.

Requirements:

• Deep Learning: Experience building CNNs, RNNs, etc. from scratch in a modern deep learning framework (Tensorflow, PyTorch, Caffe, etc.). 
• Classical ML: Experience with non-neural network deep learning models (random forests, SVM, etc.) and basic statistics. 
• Data Engineering: Experience building large-scale data processing pipelines feeding into and analyzing results from ML. 
• Experience with software development in Python. 
• BS/MS/PhD in Computer Science or a related field, or strong machine learning experience.

We base our employment decisions entirely on business needs, job requirements, and qualifications—we do not discriminate based on race, gender, religion, health, parental status, personal beliefs, veteran status, age, or any other status. We have zero tolerance for any kind of discrimination, and we are looking for candidates who share those values. Applications from women and members of underrepresented minority groups are particularly welcomed.

Here’s a small sample of some of the hard tasks we solve to accomplish our goal of developing life-saving treatments for patients:

• Developing new machine learning algorithms and architectures to model complex biological systems. 
• Translating state-of-the-art machine learning techniques designed to work on images, text, or audio into the domain of molecules. 
• Creating a large-scale distributed training and hyperparameter optimization system. 
• Using data mining and processing techniques to uncover new sources of data and clean our existing datasets. 
• Using predictive modeling to make critical decisions about which tests to run in the lab.

Requirements:

• Deep Learning: Experience building CNNs, RNNs, etc. from scratch in a modern deep learning framework (Tensorflow, PyTorch, Caffe, etc.). 
• Classical ML: Experience with non-neural network deep learning models (random forests, SVM, etc.) and basic statistics. 
• Data Engineering: Experience building large-scale data processing pipelines feeding into and analyzing results from ML. 
• Experience with software development in Python. 
• BS/MS/PhD in Computer Science or a related field, or strong machine learning experience.

We base our employment decisions entirely on business needs, job requirements, and qualifications—we do not discriminate based on race, gender, religion, health, parental status, personal beliefs, veteran status, age, or any other status. We have zero tolerance for any kind of discrimination, and we are looking for candidates who share those values. Applications from women and members of underrepresented minority groups are particularly welcomed.