Research Intern - AI Frontiers - Agentic AI Models & Synthetic Data Generation

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.

The AI Frontier Lab at Microsoft Research is seeking Research Interns to advance the state of the art in foundational model post-training, specialization and aligning models to Agentic AI capabilities such as reasoning and computer use. Our work spans both synthetic data generation and algorithmic advances in model training recipes.

 

Our lab conducts cutting-edge research in artificial intelligenace (AI) and publishes findings in top-tier venues in AI and machine learning (ML), including NeurIPS, ICLR, ICML, and others. We release models and libraries focusing on small models (e.g. Phi-3, Orca), synthetic data generation (e.g. AgentInstruct), and Agentic AI (e.g. OmniParser, AutoGen). The lab also works within Microsoft's ecosystem to impact our AI-driven technologies in multiple products.

 

We seek Research Interns with demonstrated ability for technical work and a proven record of influential publications on AI. For this role you should have a keen interest in developing synthetic data generation methods or training algorithms that enable models to take actions in a virtual world and reason more effectively, while maintaining computational efficiency.

 

Research areas of particular interest for this team include, but are not limited to:

• Developing methods to create high-quality data synthetically, with minimal human intervention.
• Agentic systems for data generation, selection and filtering.
• Developing novel training algorithms for enhancing reasoning and /or action taking.
• Reinforcement learning approaches for improving logical and mathematical reasoning.
• Exploring scaling laws between test-time and training-time compute.
• Advanced optimization techniques for efficient training of large-scale models.

Our group takes a holistic approach to improving foundational models that includes a variety of data modalities (language, vision, multi-modal, and structured data) and modern model architectures.

 

Priority will be given to candidates with a proven publication record in top-tier conferences, who have demonstrated the ability to develop original research and perform hands-on research, and who work well in a collaborative and dynamic environment.

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.

 

Additional Responsibilities

• Execute research directions that are at the forefront of innovation in AI.
• Create synergies on joint, high-impact projects in collaboration with other researchers, engineers, and product group partners.
• Work closely with other researchers in the teams on a research problem.  
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Qualifications

Required Qualifications

• Accepted or currently enrolled in a PhD program in Computer Science or related STEM field.

Other Requirements

• 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 researc