AI Scientist – Molecular Machine Learning

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled AI Scientist – Molecular Machine Learning to join our innovative and dynamic team.

AI Scientist – Molecular Machine Learning | About You

As an AI Scientist – Molecular Machine Learning, you will design and develop advanced AI/ML models that accelerate molecular property prediction, molecular generation, and drug discovery. You will apply deep learning, graph neural networks, geometric learning, transformers, and generative AI to complex molecular and chemical datasets, partnering closely with computational chemists and drug discovery scientists to solve high-impact scientific challenges. The ideal candidate is an AI/ML-first scientist with strong model development expertise and demonstrated experience applying machine learning to chemistry, molecular design, or drug discovery.

AI Scientist – Molecular Machine Learning | Day-to-Day

• Design, develop, train, and evaluate deep learning models for molecular property prediction, molecular generation, and drug discovery applications.
• Build molecular AI solutions using Graph Neural Networks (GNNs), Graph Transformers, geometric deep learning, and generative modeling techniques.
• Develop scalable AI/ML workflows using Python, PyTorch and/or JAX, optimizing models for accuracy, efficiency, and scientific relevance.
• Build and manage molecular datasets and cheminformatics workflows using RDKit and related tools, including molecular representation, preprocessing, feature generation, and model-ready dataset development.
• Develop generative modeling approaches for de novo molecular design, lead optimization, and molecular exploration, leveraging techniques such as diffusion models, flow matching, reinforcement learning, or related architectures.
• Collaborate with computational chemists, medicinal chemists, and drug discovery scientists to translate scientific problems into AI/ML approaches and generate actionable insights for molecular discovery programs.
• Evaluate and continuously improve molecular ML models using rigorous experimentation, validation, benchmarking, and reproducible research practices.

AI Scientist – Molecular Machine Learning | Skills & Experience

Originally posted on Himalayas