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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 building the next generation of proactive agents in Microsoft Teams – and the AI that powers these. These agents can take part in meetings, work for you in the background, and communicate like another colleague. We are looking to hire an applied scientist to join our team and help bring these products – and their models - Teams. We lead post-training efforts in this space, and work closely with feature teams across new innovations including conversational AI, meeting facilitation, and real-time understanding of multi-modal signals. You will partner with research, product, and engineering teams to invent and deliver the future of live communication and productivity. Your work will also impact other product groups, including MAI and Microsoft Copilot. Your work will have a direct impact on product – but as an applied science team, we also encourage exploration, and publication / patents where possible. This role is based in Cambridge (United Kingdom).
Job Responsibility:
Research, design, post-train and implement state-of-the-art multimodal models with the aim to support human communication and pro-active agents in Teams
Prepare datasets, design and implement metrics for real world scenarios in partnership with product teams and end users
Optimize LLMs for 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:
Master's degree in Computer Science, Mathematics, Electrical or Computer Engineering, or related field – or related industry experience
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 / post-training 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, post-training and LLM deployment in production
Experience with reinforcement learning of language models and other model optimization techniques
Experience with designing and collecting multimodal data to support training large language models
Experience with AML/ADO pipelines and CI tools
System development skills spanning rapid prototypes to production systems with complex dependencies