Communications Intelligence team Communications Intelligence team
The Communications Intelligence team is responsible for delivering delightful Microsoft 365 experiences powered by AI. Our charter is to research and develop natural language processing and machine learning techniques to power experiences that improve the productivity of every person and organization on the planet. We are looking for Applied Scientists who are passionate about leading and pushing forward cutting edge research and technology platforms for human communication understanding. You will work as part of a team that brings together talent in the areas of machine learning, natural language processing, information retrieval, software engineering, and trustworthy computing. We value and encourage diversity in the belief that it leads to both great workplaces and great products.
You will be expected to work on many levels - from mining massive datasets for identifying opportunities, through designing and implementing your solutions into our offline and live production systems, defining appropriate metrics to measure their effectiveness, conducting rigorous A/B experiments and impartially evaluating their results. Your coding skills will be challenged writing scalable, distributed and highly efficient components. Candidates should give evidence of their ability to write efficient and maintainable code. You will be involved in: Setting up, running and analyzing experiments
Required Master's degree in Computer Science, Engineering or related field 2+ years of experiences in natural language processing and machine learning 2+ years of experience working in software development with any of the following languages: Python, C#, C++, or Java. Preferred Ph.D. in Computer Science, Engineering or related field Publications in major HCI/ML/IR/NLP conferences would be a plus. Example: CHI, NeurIPS, ICML, KDD, WWW, SIGIR, WSDM, ACL, EMNLP Awareness and understanding of emerging research and technologies such as Machine Reading Comprehension and NLP Deep Learning approaches Experience