|Job Type:||Full Time|
Machine Learning is most exciting when it fundamentally changes how problems from other fields are approached. We are looking for Researchers and Engineers who want to apply ML to domain-specific problems, enjoy sharing their ML knowledge with experts in other fields, and are excited about building solutions to problems in the wild.
Interns will often collaborate with experts in groups across Microsoft Research, including (but not limited to) the following:
- The Cloud Infrastructure group is a multi-disciplinary team of computer scientists, physicists, and engineers, working to create the technology that will underpin the cloud of the future. Applications of machine learning include signal processing, design space exploration, and cross-layer system optimization.
- The Optics for the Cloud group, which seeks to create disruptive optical technologies for cloud computing. Realizing the potential of these technologies requires co-designing learning algorithms along with the hardware platforms they will run on, providing orders-of-magnitude improvements compared to current technologies.
- Station B aims to program biology, enabling fundamental breakthroughs in medicine, agriculture, materials and sustainable technology. It brings together experts from computer science and the bio sciences to solve these problems and uses machine learning to interpret the data collected from biological systems and predict how new techniques will work.
- Our Programming languages and software engineering projects span compilers, verification, cryptography, security and more, and AI permeates all of these.
- Design and implementation of machine learning systems for domain-specific problems, including the ingestion and pre-processing of data, choosing the right data representation and machine learning model, and measuring and tuning the performance of your system.
- Collaboration with researchers and engineers from other fields, to understand their needs and to explain your solutions.
- Deep understanding of modern machine learning techniques, for example through active research in a related PhD program or experience in research labs.
- Papers in academic conferences (NeurIPS, ICML, ICLR, AAAI or domain-specific conferences) or open source repositories with complex machine learning projects.
- Experience in building machine learning systems with standard toolkits such as TensorFlow, PyTorch, or Caffe.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.