RSDE: Machine Learning – Microsoft Research AI for Science
Description For RSDE: Machine Learning – Microsoft Research AI for Science
Microsoft Research AI for Science is seeking exceptional research software development engineers for a moonshot project in molecular biology. The role involves developing and optimizing deep learning systems for solving fundamental challenges in molecular sciences.
Key responsibilities include:
- Contributing to an ambitious research agenda in machine learning for molecular sciences
- Software development for efficient machine learning models for biomolecules
- Optimizing models for scaling, training, and inference efficiency
- Systems engineering for distributed cloud computing and data management
- Deploying ML models and transferring technology to product groups
The ideal candidate should have:
- Experience in Python software development with object-oriented design
- Experience in developing and implementing deep learning systems (e.g., PyTorch or JAX)
- Experience with high-performance or distributed computing
- Preferred skills include CUDA development, protein science or bioinformatics experience, and track record in developing novel deep learning architectures
This role offers the opportunity to work on cutting-edge AI applications in science, with potential for significant impact in the field of molecular biology. The position is based in Berlin, Germany or Cambridge, UK, with up to 50% work from home option and 0-25% travel required.
Microsoft offers a comprehensive benefits package, including industry-leading healthcare, educational resources, savings and investments opportunities, and generous time off. Join Microsoft Research AI for Science team to shape the future of AI in molecular sciences and contribute to Microsoft's mission of empowering every person and organization on the planet to achieve more.
Responsibilities For RSDE: Machine Learning – Microsoft Research AI for Science
- Contribute to and drive an ambitious, high-impact, research agenda development on machine learning in the molecular sciences
- Software development for efficient and expressive machine learning models for biomolecules. Codebase management and coordination
- Optimizing machine learning models for scaling, training and inference efficiency
- Systems engineering, e.g., efficiently working distributed cloud computing and data management system, optimizing system for efficiency and cloud costs
- Deployment of ML models to users and technology transfer to product groups
- Being fully committed to one research team and project that may take several years to come to fruition and prioritizing team success over individual research interests
Requirements For RSDE: Machine Learning – Microsoft Research AI for Science
- Experienced in Python software development with object-oriented design, software packaging and deployment
- Experienced in developing, implementing and optimizing deep learning systems (e.g., in PyTorch or JAX)
- Experienced with high-performance computing or distributed computing job and file system
- Industry experience and successfully completed projects in the area (preferred)
- Cuda development experience (preferred)
- Experience with protein science or bioinformatics (preferred)
- Experience with interpreting and including experimental data into models, e.g., Cryo-EM (preferred)
- Understanding of computational statistics and experience with generative model development (preferred)
- Experience in method development for molecular dynamics and statistical Mechanics (preferred)
- Track-record of developing and optimizing novel deep learning architectures (preferred)
Benefits For RSDE: Machine Learning – Microsoft Research AI for Science
- Industry leading healthcare
- Educational resources
- Discounts on products and services
- Savings and investments
- Maternity and paternity leave
- Generous time away
- Giving programs
- Opportunities to network and connect
