Cheminformatics and Machine Learning Engineer

Cheminformatics and Machine Learning Engineer ROCGJP00030693

A leading biotechnology company is seeking a highly motivated Cheminformatics and Machine Learning Engineer. The successful candidate will help drive research on machine learning for drug discovery, and collaborate extensively with computational and experimental scientists and researchers to deploy and deliver machine learning solutions for small molecule drug discovery. The ideal candidate has a 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).

Cheminformatics and Machine Learning Engineer Pay and Benefits:

• Hourly pay: $60-$70/hr
• Worksite: Leading biotechnology company (South San Francisco, CA 94080 - Onsite)
• W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL
• 40 hours/week, 12 Month Assignment

Cheminformatics and Machine Learning Engineer Responsibilities:

• 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.
• Closely collaborate with other scientists and researchers within Prescient 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.

Cheminformatics and Machine Learning Engineer 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).
• Expert in Python and experience with scientific software development for chemical modeling.
• Experience with RDKit or OpenEye Toolkits.
• Extensive experience working with large chemical and biological datasets, including graph, sequence, and structure-based data is a plus.
• Demonstrated experience with modern Python frameworks for deep learning like PyTorch is a plus.
• Excellent communication and interpersonal skills.
• Highly-motivated and independent self starter that is eager to collaborate.
• Basic understanding of modern machine learning methods including predictive models, generative models, and active learning as applied to small molecule drug discovery.
• A public portfolio of projects available on GitHub is a plus.
• Record of scientific excellence as evidenced by at least one first author publication in a scientific journal or machine learning conference is a plus.
• Record of machine learning research excellence as evidenced by publications in computer science and machine learning conferences (e.g. NeurIPS, ICLR, ICML) is a plus.