AI Residency Program

About

The Qualcomm AI Residency Program nurtures exceptional talent to advance the pace of AI research in Vietnam. Residents will solve real-world AI challenges and develop research to position themselves for future success. The program is designed to prepare aspiring professionals for successful careers in AI research or engineering. To date, over 120 residents have completed the program.

Applicants can join one of two tracks:

  • Research Residency Track (24 months): Residents will delve into AI research within one of three specialized areas: machine learning, computer vision, or natural language processing. Research residents will hone their analytical, writing, and presentation skills, and elevate their English proficiency to meet the standards of leading global research labs. Additionally, research-focused residents will participate in an applied research rotation to gain invaluable industry experience.
  • Engineering Residency Track (12 months): Residents will address practical AI engineering challenges in domains such as efficient AI, embedded engineering, and agentic AI. Engineering residents will develop robust engineering capabilities and engage in research rotations to become versatile, inquisitive AI engineers.

Beyond technical training, residents will have access to English language classes to enhance their communication skills, as well as a variety of soft-skills workshops. Ethics courses are also provided to ensure that residents uphold the highest standards of ethical conduct in AI research and engineering.

2025 AI Residency Program Awards

Meet the latest award winners from the Qualcomm® AI Residency Program.

COMPUTER VISION

Nguyen Trong Tung

Outstanding Resident Award

NATURAL LANGUAGE PROCESSING

Vu Thi Thi

Outstanding Resident Award / Research

COMPUTER VISION

Nguyen Minh Hung

Outstanding Resident Award / Applied Engineering

COMPUTER VISION

Nguyen Quang Binh

Substantial contributions to demo development and presentation

COMPUTER VISION

Nguyen Duc Anh

Substantial contributions to demo development and presentation

Eligibility Requirements

  • Recent graduates (within 2 years) or final-year students
  • Bachelor's or master's degree in computer science or related fields
  • Minimum GPA of 3.2/4.0, 8.0/10, or equivalent
  • Demonstrated proficiency in programming and mathematics
  • Experience with machine learning/deep learning frameworks
  • Good written and verbal English communication skills
  • Corporate internship experience is a plus

Application & Timeline

Generally, there are two Qualcomm AI Residency intakes per year for both AI research and AI engineering tracks.

The applications for Research Residency Program (RRP) Batch 16 and Engineering Residency Program (ERP) Batch 3 are open. 

Apply for AI Resident (Research) Batch 16

Apply for AI Resident (Engineering) Batch 3

  • Application: April 20 – May 15
  • Entrance Test: May 18 – 22
  • Coding Interview: June 1 - 12
  • Technical Interview: June 29 – July 3
  • Final Decision & Notification of Result: July 6 - 10
  • Offer: July 13 – August 9
  • Onboarding: August 10

Selection process

The Qualcomm AI Residency Program employs a rigorous multi-stage selection process. The standard procedure includes the following rounds:

  • Application
  • Screening
  • Entrance Test
  • Coding interview
  • Video presentation
  • Technical interview

fast-track application is available for academically outstanding students who have demonstrated exceptional achievements, such as winning high prizes in International Olympiads in Mathematics, Informatics, or prestigious international programming competitions like ACM-ICPC. Applicants eligible for the fast-track process will be contacted separately.

Qualcomm relentlessly innovates to deliver intelligent computing everywhere, helping the world tackle some of its most important challenges. Our leading-edge AI, high performance, low-power computing, and unrivaled connectivity deliver proven solutions that transform major industries. At Qualcomm, we are engineering human progress.

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