Our client is 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 for applying and implementing 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 development including QSAR and ADMET. Strong understanding of ML fundamentals, models, and algorithms. Proficiency in modern AI tech stack, preprocessing data, and strong Pytorch. Benefits Salary: Up to €250k DOE Equity Comprehensive benefits package Interested? Apply now in the link below. #J-18808-Ljbffr Alldus International Consulting Ltd
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