About the role#
As a Machine Learning and Artificial Intelligence Engineering Intern, you will work within a research environment to build tools and solutions for mobile and embedded platforms. These platforms power robotics, smartphones, IoT devices, and autonomous vehicles. You will collaborate with multi-disciplinary teams of researchers and developers, gaining exposure to hardware accelerators and system-on-chip compute. Projects may involve AI infrastructure, distributed inference, compiler technologies, GPU acceleration, and performance optimization.
What you'll do#
- Design, develop, and test software for machine learning tools and frameworks.
- Collaborate with internal teams in a research setting.
- Work with popular neural network frameworks to build efficient models for edge devices.
- Develop solutions for mobile and embedded machine learning platforms.
- Optimize models for edge devices to improve performance and efficiency.
What you'll need#
- Current enrollment in a bachelor’s, master’s, or Ph.D. program in computer science, computer engineering, electrical engineering, or a related field.
- Expected graduation date of November 2027 or later.
- Availability for 11 to 14 weeks during Summer 2027.
- At least 1 year of experience with Python, C, or C++.
- Proficiency in deep neural networks, machine learning algorithms, and architectures.
- Experience with ML frameworks such as TensorFlow, TFLite, or PyTorch.
- Knowledge of compiler frameworks like LLVM, GCC, TVM, or XLA.
- Familiarity with AI infrastructure, inference systems, distributed computing, runtime systems, GPU programming, CUDA, Kubernetes, or MLIR.
- Understanding of linear algebra, fast math libraries, and object-oriented software design.
- Theoretical knowledge of model compression, quantization, and optimization.
- Familiarity with on-device training, transfer learning, federated learning, NLP, computer vision, or generative models.
- Experience with ML data pipelines and backend or frontend applications.
- Research excellence with publications in venues such as NeurIPS, CVPR, ICML, ICLR, or ICCV is a plus.
Location & details#
- This is a full-time, paid, on-site internship.
- Available locations include San Diego, CA; Austin, TX; Boxborough, MA; New Jersey; New York City, NY; Raleigh, NC; and Santa Clara, CA.
- Relocation coverage and furnished housing are provided.
About Qualcomm
Qualcomm manufactures semiconductors and develops computing technologies. Founded in 1985, the company maintains its headquarters in San Diego. It serves markets including mobile, automotive, and the internet of things. The organization employs more than 10,000 people and operates as a public company.
How to get in at Qualcomm
Applying to Qualcomm early provides a distinct advantage because recruiters review applications before the volume of candidates becomes unmanageable. Intern Insider sends an instant alert the moment a role matching your target is published, which helps you apply among the first. This timing ensures your materials are seen while the team is still actively building their shortlist. Reaching out to the right people often yields better results than submitting through a general portal. Intern Insider surfaces the recruiters behind Qualcomm roles so you can contact them directly to ask about the position or a referral. This approach materially improves your response rates compared to waiting in a queue.
