Research Intern - AI-driven Hardware Design

Microsoft; Redmond (WA); On-site; USD 56,804 - 112,939; Full time

Job summary

Microsoft is offering a Research Internship based in Redmond, Washington, where you can work on cutting-edge AI infrastructure development. This dynamic role requires collaboration with world-class researchers and aims to solve complex challenges.

Ideal candidates are currently enrolled in a relevant degree program and possess strong analytical and communication skills. During the internship, you will be involved in research, development, and innovation to advance AI and hardware practical applications.

Qualifications

• Currently enrolled in a degree program related to Computer Science or Engineering.
• Experience in AI hardware components such as GPUs and TPUs is beneficial.
• Ability to work independently and collaboratively.

Responsibilities

• Design and develop AI-driven infrastructure.
• Conduct research on trends in AI and hardware.
• Collaborate with cross-functional teams.
• Prepare documentation and present findings.

Skills

Analytical skills

Problem-solving skills

Communication skills

Experience in simulation modeling

Proficient understanding of AI and machine learning

Knowledge of hardware design and architecture

Education

Currently enrolled in bachelor's, master's, or Ph.D. program in relevant field

Tools

Python

C++

MATLAB

TensorFlow

PyTorch

Job description

Overview

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.

As a Research Intern at Microsoft Research, you will be at the forefront of developing and implementing cutting‑edge Artificial Intelligence (AI)-driven AI infrastructure. This role is ideal for candidates who are passionate about AI software and hardware development. You will collaborate with a team of world‑class researchers and engineers in Vancouver, Canada, and Redmond, Washington to create the next generation of AI infrastructure that enhances the efficiency and effectiveness of AI.

Qualifications

Required Qualifications

• Currently enrolled in a bachelor's, master's, or Ph.D. program in Computer Science, Electrical Engineering, Machine learning, Mathematics, or a related 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 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.

Preferred Qualifications

• Proficient analytical and problem‑solving skills and communication skills, both written and verbal.
• Ability to work independently and collaboratively in a dynamic research environment.
• Proficient understanding of AI and machine learning concepts, especially in relation to hardware infrastructure.
• Experience in simulation modeling and software development (e.g., Python, C++, MATLAB).
• Research expertise with AI hardware components such as GPUs, TPUs, and neuromorphic chips. Hardware RTL development (SystemVerilog, Chisel, Bluespec) is a plus.
• Experience with machine learning frameworks (TensorFlow, PyTorch).
• Deep Knowledge of hardware design and architecture.
• Prior research or project experience in AI or hardware simulation.

Pay and Benefits

Applied Sciences IC2 - The base pay range for this internship is USD $5,090 - $10,120 per month. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $6,690 - $11,030 per month.

Applied Sciences IC3 - The base pay range for this internship is USD $6,290 - $12,170 per month. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $8,060 - $13,240 per month.

Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-intern-pay

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.

As a Research Intern for this position, you will:

• Development and Implementation: Design and develop AI-driven AI infrastructure. Implement prototypes and conduct simulations to test and validate them.
• Research and Analysis: Conduct thorough research on emerging trends in AI software and hardware infrastructure.
• Collaboration: Work closely with cross‑functional teams, including hardware engineers, software developers, and data scientists, to integrate your ideas with existing and future AI projects.
• Documentation and Reporting: Prepare detailed documentation of simulations, methodologies, and findings. Present results and insights to team members and stakeholders.
• Innovation and Problem‑Solving: Identify challenges and bottlenecks in AI infrastructure and propose innovative solutions.