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Microsoft Teams is the hub for teamwork that integrates all the people, content, and tools your team needs to be more engaged and effective. It is core to Microsoft’s modern work, modern life & modern education value prop. We are reinventing the way people communicate and work together across the globe. We are looking to hire a Senior Applied Scientist to join the science team responsible for some of the Artificial Intelligence innovations and experiences being delivered within Microsoft Teams and related products. The team works on state-of-the-art AI models and leverages innovation in their architecture, training, fine-tuning, distillation and general design patterns to build innovative features to bring value to our customers. You will partner with research, product and engineering teams to invent and deliver the future for Microsoft Teams, Microsoft Copilot and other AI products.
Job Responsibility:
Research, design, implement, adapt, train, fine tune or distil state-of-the-art multimodal models with the aim to support human communication in Teams
Prepare datasets, design and implement metrics and optimize model efficiency and performance
Collaborate closely with other groups (research, engineering and product groups) within the wider Microsoft organization, to create the next generation of AI innovation in our products and services
Embody Microsoft culture and values
Requirements:
Undergraduate or Master’s degree in Computer Science, Mathematics, Electrical or Computer Engineering, or related field
2+ years practical ML Engineering and Python coding experience leveraging PyTorch, TensorFlow or similar framework, within large code repositories and in collaboration with additional team members
2+ years’ practical experience in designing, training or fine-tuning transformer-based models or LLMs
2+ years’ experience of working with language, transcription, audio or multimodal applications (e.g., combining audio and video, text and audio)
Excellent analytical, coding, communication, and collaborative skills
Nice to have:
PhD in Computer Science, Mathematics, Electrical or Computer Engineering, or related field
Industry experience delivering real-world solutions
Experience with large-scale distributed training and deployment
Experience with reinforcement learning of language models, quantization and other model optimization techniques
Experience with audio (speech to speech) foundation models, multimodal conversational models
Experience with AML/ADO pipelines and CI tools
System development skills spanning rapid prototypes to production systems with complex dependencies
A track record of innovation in AI evidenced by scientific publications, patents or contributions to product features