Research Intern - Microsoft Research and Outlook

Job Description

Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment. This position is for a Research Internship with the Intelligent Networked Systems group in MSR’s Redmond Lab, in partnership with the product group Experiences and Devices. Our group conducts cutting edge research in networked systems, including edge AI, wide-area networking, and wireless technologies. You will be collaborating with a product team in Experiences and Devices who are creating product experiences driven by cutting edge technology that will help millions of people be more productive and create a sense of delight, making the impossible possible. This role focuses on enhancing email systems like Outlook through reasoning with deep contextual awareness of the user’s work and preferences with the goal of delivering personalized, real-time assistance to the millions of users who rely on Outlook every day. This is an exciting opportunity to contribute to cutting-edge AI research while solving critical challenges of scalability, latency, and efficiency in user-facing systems.

Requirements

• Currently pursuing a PhD in Computer Science, Machine Learning, or a related field.
• Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship.
• In addition to the qualifications below, you’ll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter.
• Proven foundation in natural language processing (NLP) and deep learning.
• Familiarity with LLMs and their applications in real-world systems.
• Proven experience with lightweight machine learning techniques and their integration with deep learning models.
• Demonstrated proficiency in mixed-technologies and AI prototyping Knowledge of scalable architectures, distributed systems, or edge computing.
• Can demonstrate at least 1 year experience conducting original research in (or closely related to) Natural Language Processing, ML and Deep Learning, Distributed Systems and Cloud computing, scalable system design, Programming proficiency in Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) Demonstrates the ability to think unconventionally to derive creative and innovative solutions.
• Experience working on large-scale systems handling high user and data volumes.
• Demonstrated ability to optimize latency and computational efficiency in real-time applications.
• Published research in top-tier AI/ML or NLP conferences (e.g., NeurIPS, ACL, EMNLP).

Responsibilities

• Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world’s best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer.
• Conduct research on scalable LLM architectures for email prioritization.
• Explore opportunities to blend diverse methodologies for maximizing efficiency and contextual understanding.
• Collaborate across disciplines to ensure successful integration of next-generation technologies into operational systems.
• Continuously assess and improve system performance to maintain robustness and efficiency under real-world conditions.
• Provide insights and contribute to breakthroughs through prototypes, thought leadership, and knowledge sharing.
• By the end of your internship you will deliver a working prototype, demonstrating email prioritization for large scale systems.
• You will also be working towards submitting a patent application and publishing a research paper summarizing the challenges of scaling LLMs for email prioritization, the design of the solution and experimental findings.

Benefits

• Industry leading healthcare
• Educational resources
• Discounts on products and services
• Savings and investments
• Maternity and paternity leave
• Generous time away
• Giving programs
• Opportunities to network and connect