Microsoft Teams is looking to reinvent the way people communicate and work together by integrating AI, specifically leveraging foundation models for next-generation innovations and experiences in CoPilot and other generative AI products.
Requirements
- 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C-Sharp, Java, JavaScript, or Python
- 2+ years of experience in Android or iOS Mobile App Development.
- 3+ years of experience in machine learning.
- Experience with ML tools like Pytorch and TensorFlow.
- Experience developing applications using prompt engineering, fine tuning, Open AI or Azure Open AI APIs.
- System development experience with exposure to rapid research prototypes and carefully architected complex systems.
Responsibilities
- Collaborate with a multi-functional group to deliver next generation innovations and experiences leveraging, fine tuning and prompt engineering foundation models.
- Partner with product and engineering teams to invent and deliver on the future for Microsoft CoPilot and other generative AI products.
- Conduct applied science experiments, create and validate metrics, develop ML pipeline and modeling algorithm in the area of Large Language Models, Natural Language Processing, Information Retrieval, and Machine Learning.
- Develop and deploy conversational and language understanding models at scale.
- Follow and advance best practices for Responsible AI and Privacy Preserving Machine Learning.
- Collaborate closely with Microsoft Research, Microsoft AI groups, Microsoft Azure, AI platform teams, and product teams to create the next generation of AI innovation in our products and services.
Other
- 3 days / week in-office
- Collaborates across multiple disciplines to deliver innovation.
- Helps make and communicate priorities and tradeoffs to lay out a path for achieving a vision.
- Can inspire without authority across teams and motivate individuals to work together towards common goals.
- Thrives in a bit of chaos then creates the structure needed to execute smoothly at scale.
