Top Biotech Machine Learning Engineer Jobs

The Senior Machine Learning Research Engineer will develop and deploy deep learning pipelines, optimize model training, and collaborate with scientists to enhance AI/ML capabilities for cancer detection.

Lead development of machine learning models for drug discovery, integrating ML with molecular modeling to enhance molecular design and optimization approaches.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

Develop innovative machine learning algorithms for modeling proteins, collaborate with biologists, and refine predictions through experiments.

Develop machine learning models to predict molecular properties, create novel algorithms for new molecules, and collaborate with chemists and engineers to optimize performance and integrate models into software.

As a Scientist in Machine Learning, you will develop novel models for RNA structure and drug targeting, advancing the R&D platform and collaborating with interdisciplinary teams.

Lead development and integration of AI/ML approaches for drug discovery, partnering with chemists and biologists to drive Go/No-Go decisions, create active learning cycles, mentor staff, and evaluate external technologies to improve ADMET and lead optimization outcomes.

Lead the development of scalable AI solutions for Novartis, integrating advanced machine learning models while collaborating with teams in the US and India.

As a Senior AI/ML Engineer, you will design and deploy LLM systems, collaborate with cross-functional teams, and manage model deployment in production environments.

The ML Research Engineer will develop training pipelines for atomistic simulation models and collaborate with researchers to optimize training workflows.