Applied Scientist Intern: Live Proactive Meeting Agents

Overview

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 PhD (or published MSc) candidate for a 12-week internship (ideally from February 2026) to join CMD Labs – an applied science team within Microsoft Teams – to work on the next generation of live proactive agents for meetings. Specifically, we are interested in researching and developing agents that can proactively take part in meetings and provide help and guidance in a range of live scenarios. We are expecting the candidate to explore techniques including Reinforcement Learning in simulated environments to train models, and will be deploying and testing these in live Teams scenarios.

The intern will be fully onboarded onto our current science and production code base and be expected to investigate, propose, implement and test new algorithms and approaches in this area – solving problems of direct relevance to product. The intern will also be expected to present results internally at the end of the position and write up the work for publication in a leading academic AI conference (e.g. ICML, NeurIPS, ACL, CVPR, ICCV).

You will partner with research, product and engineering teams to invent and deliver the future for Microsoft Teams, Microsoft Copilot and other AI products. 

This role is based in Cambridge (United Kingdom).

Our culture is inclusive and collaborative; our team members come from diverse backgrounds, are respectful to one another and achieve impact by building on each other’s strengths and skills. We focus our energy on AI projects that are likely to have high impact on our products and bring high value to our customers. Our team has a strong sense of bias for action and accountability and provides its members with many opportunities for learning and career growth.

Responsibilities

• Conduct experiments, create and validate metrics, and train candidate models (LLMs) for proactive behavior in live meeting scenarios.
• Collaborate closely with CMD Labs researchers and engineers to leverage existing assets, datasets, and ensure results can be leveraged back into the product.
• Embody Microsoft culture and values.
  
  

Qualifications

Required

• Currently enrolled in a PhD program (or published candidate in MSc program) in Computer Science, Electrical or Computer Engineering, Statistics, or a related field.
• Practical experience in training, fine-tuning, LLMs particularly using Reinforcement Learning in synthetic training environments.
• Practical Python coding experience leveraging PyTorch or TensorFlow or similar framework.
• Excellent analytical, coding, communication, and collaborative skills.
  
  

Preferred    

• Field of research and publications directly related to language modeling, LLMs, Reinforcement learning.
• Experience in model quantization, pruning or distillation.
• Experience working in the domain of live chat or meeting scenarios.
  
  

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.