Microsoft Research Intern - Azure Front Door Edge Actions Low Latency Compute 

Taiwan, Taoyuan City 

320472256

• Currently pursuing a PhD in Computer Science, Machine Learning, 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.

• Proficient foundations with ML models, 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
• Expertise in scalable architectures, distributed systems, or edge computing.
• 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 systems, networking, and AI/ML conferences.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

• Develop a suite of lightweight filters packaged as Edge Actions for AI applications such as video analytics, LLM queries, and personal assistants.
• Conduct research on orchestrating AI applications between the Azure Front Door edge and Azure region.
• Explore opportunities to trade off compute and bandwidth efficiency with latency and accuracy benefits.
• 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 Edge Actions at scale for real-world use cases.
• You will also be working towards submitting a patent application and publishing a research paper summarizing the design of the solution and experimental findings.