Overview
At Microsoft Research AI for Science we believe deep learning has the potential to transform scientific modelling and discovery crucial for solving the most pressing problems facing society, including sustainable materials and discovery of new drugs.
For our labs in Amsterdam (NL), Cambridge (UK) and Berlin (DE) we seek several highly motivated research engineers with expertise in machine learning and/or distributed systems to join our projects on the intersection of machine learning and density functional theory (DFT) team (What is DFT?), small molecules discovery (our research on small molecules), and our centralized engineering team. Our team encompasses people from multiple disciplines across machine learning, engineering, and the natural sciences, who work together closely on well-defined and challenging goals. If you have strong machine learning expertise and enjoy designing and creating tools for scalable machine learning research for the natural sciences, please apply.
This post will be open until the positions are filled.
Responsibilities
- Develop and maintain tools, models and technologies for building, training, optimizing and scaling machine learning solutions.
- Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data.
- Build and optimize distributed data processing and model building pipelines.
- Prepare and maintain open-source releases and releases for internal and external beta testers.
- Work cross-functionally with machine learning researchers, engineers and researchers from the natural sciences.
- Maintain high standards in code quality and software design.
- Document and share best practices across the organization.
Qualifications
Required qualifications:
- Completed MSc in computer science, machine learning, AI or a related area.
- Proficiency in collaborative software engineering in Python.
- Familiarity with Linux and the open-source ecosystem.
- In-depth understanding of open-source machine learning frameworks such as PyTorch and/or Jax.
- Experience in designing, developing and deploying ML systems.
- Experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs.
- Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds.
Qualifications that are considered a plus, but are not strictly required:
- PhD degree in computer science, machine learning, AI or a related field, or comparable industry experience in working with machine learning and large datasets.
- Experience working with major cloud platforms and/or HPC.
- Experience developing high-performance scientific software.
- Experience with LLMs and/or frameworks like ggml, llama.cpp, vllm
#Research #AI for Science
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about
requesting accommodations. 
