The Business & Industry Copilots group is a rapidly growing organization that is responsible for the Microsoft Dynamics 365 suite of products, Power Apps, Power Automate, Dataverse, AI Builder, Microsoft Industry Solution and more. Microsoft is considered one of the leaders in Software as a Service in the world of business applications and this organization is at the heart of how business applications are designed and delivered.
This is an exciting time to join our group Customer Zero Engineering and work on something highly strategic to Microsoft. The goal of Customer Zero Engineering is to build the next generation of our applications running on Dynamics 365, AI, Copilot, and several other Microsoft cloud services to deliver high value, complete, and Copilot-enabled application scenarios across all devices and form factors. We innovate quickly and collaborate closely with our partners and customers in an agile, high-energy environment. Leveraging the scalability and value from Azure & Power Platform, we ensure our solutions are robust and efficient. If the opportunity to collaborate with a diverse engineering team, on enabling end-to-end business scenarios using cutting-edge technologies and to solve challenging problems for large scale 24x7 business SaaS applications excite you, please come and talk to us!
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Job Description:
We are looking for a highly motivated and skilled Machine Learning Scientist II / MLOps Engineer II to join our team. The ideal candidate will have a strong background in machine learning, MLOps/AIOPs, and software engineering practices, and will be responsible for the development, deployment, and operationalization of machine learning models at scale. This role will work closely with data scientists, software engineers, and product teams to ensure the models are secure, reliable, and performant.