Senior Scientific Software Engineer (Drug Discovery)

Join our team as a Senior Scientific Software Engineer, where you will contribute to the development of computational chemistry tools and bridge the gap from R&D prototypes to stable, production-ready implementations. You will work closely with a team of computational chemists, physicists, AI experts, and software engineers to create clean software and enhance our portfolio of capabilities. This role requires a strong understanding of the technical challenges and scientific concepts in the drug discovery space, as well as deep experience in building efficient and maintainable implementations of AI- and physics-based simulation software.

• Contribuer au développement d'outils de chimie computationnelle et à la transition des prototypes R&D vers des implémentations stables et prêtes à la production.
• Maintenir et étendre les packages logiciels scientifiques existants, et diriger le cycle de vie complet de nouveaux logiciels.
• Collaborer avec l'équipe d'ingénierie pour déployer ces modules dans la plateforme de simulation de SandboxAQ.
• Ability to rapidly write good quality code while not letting the perfect become the enemy of the good
• At least 5 years professional experience in software development, designing and developing well-maintained software systems and collaborating with domain experts to design solutions that meet their needs
• Desire to work in a fast-paced team with diverse professional experiences and viewpoints
• Experience with ML libraries like PyTorch
• Experience using LLM tools and coding harnessed to build quickly while producing understandable, secure, maintainable code that’s a strong foundation for long-term development
• Experience with relevant development tools and environments (git, Unix/Linux, cloud-based platforms, containerization)
• Strong Python proficiency including experience with numeric and performance libraries like Numpy
• Ability to devise, communicate internally and own technical roadmaps, in a self-directed environment
• Bachelor's degree in a relevant scientific discipline (for example physics, chemistry, biology, or computer science)
• Experience developing software for scientific applications
• Familiarity with open source scientific and molecular libraries such as OpenMM, RDKit, Scikit-learn
• Experience with modern deep learning architectures
• Experience with the drug discovery and drug development processes