Key Responsibilities

About This Role

A*STAR seeks a Scientific Platform Engineer to build scalable, enterprise-grade software systems for AI in Drug Discovery by collaborating with scientists and translating research workflows into robust data-intensive platforms.

Responsibilities

• Collaborate with Principal Investigators and research teams to understand computational and experimental workflows.
• Translate scientific requirements into robust software architectures for production systems.
• Transform research code, prototypes, and experimental pipelines into scalable maintainable software platforms.
• Develop reusable tools and services enabling operationalization of new algorithms and data workflows.
• Build systems capable of handling large-scale multimodal scientific datasets including chemical libraries, assay readouts, omics data, and biomedical literature.
• Establish best practices for reproducibility, versioning, testing, and deployment of scientific software.

Requirements

• Master's degree in Computer Science, Software Engineering, Biomedical Engineering, Computational Chemistry, Bioinformatics, or related disciplines.
• Strong programming skills in Python, C++, Java, and other languages.
• Expertise in scientific domains such as bioinformatics, cheminformatics, genomics, and medical imaging.
• Experience building infrastructure for data science and ML workflows using frameworks like PyTorch, TensorFlow.
• Experience with scientific libraries such as scikit-learn and Pandas.
• Expertise in cloud platforms including Google Cloud Platform (GCP) and AWS.
• Experience working in drug discovery, biotechnology, or biomedical research environments.
• Experience managing large multimodal datasets in scientific contexts.