Lead Machine Learning Scientist – Computational Chemistry

San Francisco, California

Computational Chemistry

Permanent

Our client are a growing Biotech startup and they are hiring a Lead Machine Learning Scientist to join the team on a hybrid working model in South San Francisco. The successful candidate will be responsible to apply and implement machine learning techniques to accelerate the company’s unique target-agnostic, multimodal approach to drug discovery.

Responsibilities

Design and develop novel ML models and components for the company’s innovative multimodal phenotypic approach to drug discovery.
Partner with cancer biologists, biostatisticians and wet-lab specialists to determine product requirements and functionality.
Process research papers, evaluate & integrate commercial & publicly available frameworks, methods & tools.
Take proof of concept to implementation and scale them with robust ML engineering pipelines.
Proactively contribute to the planning of the business roadmap.

Skillset

5+ years of post graduate experience in hands on development in Machine Learning and deep math powered principles for drug discovery.
Experience in Computational chemistry applied to med-chem MLS development for drug discovery.
Experienced with computational chemistry packages.
Proficiency in small molecule developing including, QSAR and ADMET.
Strong understanding of ML Fundamentals, models and algorithms.
Proficiency in Modern AI Tech stack, preprocessing data, strong Pytorch.