Research Intern - AI Systems & Architecture

Overview of the Research Intern - AI Systems & Architecture Role at Microsoft

Research Internships at Microsoft provide a dynamic environment for research careers, supported by a network of world-class research labs. These labs are led by globally-recognized scientists and engineers who drive innovation across various scientific and technical disciplines, aiming to solve complex challenges in fields like computing, healthcare, economics, and the environment.

The advancement of Artificial Intelligence increasingly relies on breakthroughs in systems and architecture, where the co-design of hardware, models, and software is crucial for efficient scaling. This Research Intern - AI Systems & Architecture position offers a unique opportunity to explore next-generation AI systems through performance modeling, architectural analysis, and emerging inference mechanisms. Research Interns will delve into topics such as disaggregated inference, sparse/expert model scaling, and innovative accelerator, memory-architecture, and interconnect technologies. This role is perfectly suited for students who are passionate about gaining an end-to-end understanding of AI systems and contributing to the foundational architectural designs of future intelligent datacenters.

Key Responsibilities for Research Interns

Research Interns at Microsoft translate inquiry and theory into practical application. They learn, collaborate, and network with fellow doctoral candidates and leading researchers, contributing to their own career growth while making significant strides in exciting research and development. During the typical 12-week internship, Research Interns are paired with experienced mentors. They are expected to:

• Collaborate with other Research Interns and established researchers.
• Present their findings to the research community.
• Actively contribute to the vibrant life and intellectual discourse of the research community.

Internships are available year-round across all research areas, though they commonly commence in the summer.

Additional Responsibilities

• Investigate emerging AI system architectures and analyze the interaction between hardware, software, and model behavior across large-scale inference workloads.
• Develop and evaluate analytical or simulation-based performance models to pinpoint system bottlenecks, scalability limitations, and potential optimization avenues.
• Prototype or assess novel inference mechanisms, including disaggregated execution, sparse/expert model scaling, and hierarchical attention techniques.
• Explore advanced accelerator, memory-architecture, and interconnect technologies, evaluating their architectural trade-offs and cost implications.
• Conduct experiments, synthesize research findings, and clearly communicate results to mentors and collaborating researchers.
• Collaborate effectively with fellow interns and researchers to advance new ideas in AI systems and architectural design.

Required Qualifications

• Currently enrolled in a PhD program in Computer Science, Electrical/Computer Engineering, or a closely related field.

Other Requirements

• Research Interns must be physically located at their manager’s Microsoft worksite location for the entire duration of their internship.
• Applicants are required to submit a minimum of two reference letters, a cover letter, and any relevant work or research samples. Reference letter requests may be sent after application submission, and candidates are advised to alert their letter writers in advance.

Preferred Qualifications

• Demonstrated research experience in areas such as computer architecture, AI/ML systems, performance modeling, distributed systems, or hardware-software co-design.
• Proficiency in programming with Python and C/C++, coupled with experience in building prototypes, simulators, or performance analysis tools.
• Familiarity with modern AI workloads and deep learning frameworks, such as PyTorch.
• Proven ability to define and pursue original research directions within AI systems or architecture.
• Strong ability to collaborate effectively with researchers from diverse disciplines and thrive in cross-group, cross-cultural environments.
• Excellent communication and presentation skills, essential for sharing complex technical insights.
• A creative mindset and an innovative approach to solving system and architecture challenges.
• Experience with specific tools and technologies like PyTorch, CUDA, Triton, or various performance-simulation tools.
• Background in large-scale system design, AI inference bottleneck analysis, or modeling cost/performance tradeoffs.
• Solid understanding of accelerator, memory-system, or interconnect design principles.

Compensation Information

The base pay for this internship generally ranges from USD $6,710 to $13,270 per month. For specific work locations within the San Francisco Bay area and New York City metropolitan area, the base pay range is USD $8,760 to $14,360 per month. Additional benefits and compensation may apply and vary based on employment nature and country. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until filled.

Key Skills/Competency

• AI Systems Architecture
• Performance Modeling
• Hardware-Software Co-design
• Deep Learning Frameworks
• Distributed Systems
• C/C++ Programming
• Python Programming
• Accelerator Technologies
• Memory Architecture
• Inference Mechanisms