Key Responsibilities
- Develop and optimize machine learning models for large-scale applications in drug discovery and molecular design
- Collaborate with research scientists to implement novel algorithms and improve model performance
- Design and maintain scalable training pipelines for deep learning models on high-performance computing clusters
- Benchmark and validate models against baseline approaches, ensuring reproducibility and robustness
- Contribute to open-source projects and publish findings in peer-reviewed venues
- Optimize inference workflows for deployment in production environments
Requirements
- Master's or PhD in Computer Science, ML, or a related field with hands-on research experience
- Strong proficiency in Python and deep learning frameworks (PyTorch/TensorFlow)
- Experience with distributed training (Horovod, Ray, or similar) and GPU acceleration
- Familiarity with molecular modeling, graph neural networks, or generative AI techniques
- Publications or contributions to ML/AI research communities are a plus