We are the Microsoft 365 Substrate team, the engine that powers Office 365 and many other critical products within Microsoft Cloud. Office 365 is the largest collaboration service in the world with 100s of millions of consumer/enterprise mailboxes, documents and conversations, it represents the world's largest platform of human collaboration for personal, business and educational use. We are a massively distributed cloud service with O(exabyte) data handled by O(300K) servers in O(300) data-centers around the entire globe. By incorporating machine learning techniques and data analytics into the services we deliver, we enable highly personalized, self-learning experiences and suggestions that make each user be more productive every time they use the service.
As part of this team, we have bold goals: we want to build AI/ML scenarios and platform with cutting edge tech that encompasses data collection, feature engineering, model training, extensive experimentation, deploying, productization, and monitoring of machine learning models involving text, image, audio/video. Our scenarios require use of the latest machine reading comprehension, QnA, Deep Learning, NLU and NLP to improve and automate business process and generate knowledge and insights for M365.
You don't want to miss out on the opportunity to shape the future of intelligent applications in Office 365! We are looking for an applied Scientist to work on the AI/ML initiatives for the organization for scenarios that have a tremendous impact on the Office 365 business. The candidate should be knowledgeable in AI techniques, with a focus on problem-solving, rather than a particular method or tool kit. The candidate should be open to exploring various cutting-edge AI technologies and applying them on large scale data. The candidate has demonstrated experience helping build and ship machine-learning models to customers based on real-world scenarios.
* Familiarity with one or more machine learning and NLP frameworks such as Scikit Learn, PyTorch , Tensor Flow Spark, NLTK, CNTK.
* Solid experience and understanding in all the areas of the Machine Learning Model Life Cycle
* Skill and Experiences in Data science, Natural Language Understanding, Machine Learning, Deep Learning, Reinforcement learning
* Strong coding and development skills.
* Ability to effectively deal with ambiguity
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
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. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
* Work with a team of applied scientists, data scientists and engineers that are building AI/ML scenarios and platforms in O365.
* Be customer-focused with a commitment to high quality end to end services through livesiteand quality-first culture
* Work independently and collaboratively with other research and product teams across Microsoft to build end-to-end intelligent office experiences involving machine reading comprehension, enterprise knowledge base and knowledge graph systems, semantic experiences etc.
* Communicate complex topic to non-technical audiences and understand the implications of complex business, legal, and regulatory issues on technology and technical deliverables.
* Collaborate inside and outside the team, and across remote development locations
* Have fun and learn new things
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