Machine Learning Engineer

No sub-contracting !!! Only direct local W/2's as onsite(THIS REQUIRES ONSITE IN SOUTH SAN FRANCISCO!) is required for:

We are seeking a highly motivated Machine Learning Scientist to join clients Research and Early Development to help drive research on Machine Learning for Drug Discovery. The successful candidate will collaborate extensively with computational and experimental scientists and researchers across dept. to deploy and deliver machine learning solutions for small molecule drug discovery.

The Role

Implement cheminformatics and computational chemistry-based methods to support our Lab-in-the-Loop efforts for small molecule drug discovery.
Deploy and deliver technical solutions at the intersection of computational chemistry, software engineering, and machine learning, supporting small molecule design across broader for clients.
Closely collaborate with other scientists and researchers within client to build impactful technologies for drug discovery research.
Build and scale machine learning techniques to massive datasets and aid in the deployment of novel machine learning algorithms with experimental collaborators.
Contribute to and drive publications, present results at internal and external scientific conferences, and help make code and workflows open source.

Desired Qualifications

BS, MS, or PhD degree in the physical sciences (e.g. Chemistry, Physics, Chemical Engineering) or quantitative field (e.g. Computer Science, Statistics, Applied Mathematics) or equivalent industry research experience (5+ years for BS, 3+ years for MS).
Excellent communication and interpersonal skills.
Highly-motivated and independent self starter that is eager to collaborate.
Expert in Python and experience with scientific software development for chemical modeling.
Experience with RDKit or OpenEye Toolkits.
Basic understanding of modern machine learning methods including predictive models, generative models, and active learning as applied to small molecule drug discovery.

Additional Qualifications

Candidates may additionally have, but are not required to have:
Public portfolio of projects available on GitHub
Extensive experience working with large chemical and biological datasets, including graph, sequence, and structure-based data
Demonstrated experience with modern Python frameworks for deep learning like PyTorch
Record of scientific excellence as evidenced by at least one first author publication in a scientific journal or machine learning conference
Record of machine learning research excellence as evidenced by publications in computer science and machine learning conferences (e.g. NeurIPS, ICLR, ICML).