Machine Learning & Artificial Intelligence Engineering Internship – Summer 2027

Responsibilities

• Help build best‑in‑class solutions and tools that enable state‑of‑the‑art technologies for next‑generation mobile and embedded machine‑learning platforms.
• Work in a dynamic research environment as part of a multi‑disciplinary team of researchers and software developers.
• Collaborate with internal teams and use popular neural‑network frameworks while gaining exposure to Qualcomm’s SoC compute and ML hardware accelerators.
• Contribute to projects focused on AI systems infrastructure, distributed inference platforms, compiler technologies, runtime systems, GPU acceleration, model serving, performance optimization, and large‑scale deployment of machine‑learning workloads.
• Design, develop, and test software for machine‑learning tools and frameworks that make models smaller and more efficient for edge devices.

Minimum Qualifications

• Currently enrolled in a bachelor’s, master’s, or Ph.D. degree program in computer engineering, computer science, electrical engineering, or a related field.
• Must be available for 11–14 weeks during Summer 2027 (May–September).
• Expected graduation date of November 2027 or later.
• 1+ years of experience with programming languages such as C, C++, or Python.

Preferred Qualifications

• Currently enrolled in a master’s or Ph.D. program in computer engineering, computer science, electrical engineering, or a related field.
• Anticipated graduation between November 2027 and June 2028.
• Proficiency in deep neural networks, machine‑learning algorithms, and architectures (CNNs, RNNs, LSTMs).
• Experience with ML frameworks such as TensorFlow, TFLite, and PyTorch.
• Skills in neural‑network programming, video/image processing, and application development.
• Knowledge of compiler frameworks (LLVM, GCC, TVM, XLA) and parallel computing.
• Experience with AI infrastructure, inference systems, distributed computing, runtime systems, GPU programming (CUDA), Kubernetes, MLIR, or performance optimization of machine‑learning workloads.
• Understanding of linear‑algebra operations and fast‑math libraries.
• Theoretical knowledge of ML, deep learning, model compression, quantization, and optimization.
• Experience with reinforcement learning, neural architecture search, kernel optimization, Bayesian optimization.
• Familiarity with on‑device training, transfer learning, personalization, federated learning, NLP, and ML security/privacy.
• Experience with deep generative models, audio/speech processing, computer vision, and wireless communication.
• Background in ML data pipelines, data management, and backend/frontend applications.
• Research excellence with publications in venues such as NeurIPS, CVPR, ICML, ICLR, or ICCV.
• Experience in object‑oriented software design (OOSD).

Benefits

• Competitive hourly pay.
• Accrued vacation time.
• Relocation coverage.
• Furnished housing accommodations for the duration of the internship.
• Professional development workshops, social events, cross‑functional speaker sessions, and an executive speaker series.
• Mentorship and visibility to project and team leaders.
• Access to the broader Qualcomm employee community.
• Potential eligibility for annual discretionary bonus and RSU grants (subject to employment status).
• Internship locations may include Austin, Boulder, Boxborough, Bridgewater, Chandler, Irvine, New York City, Louisville, Raleigh, San Diego, Santa Clara, and Seattle.

Pay

The hourly pay range for this internship is $17.00 – $98.00, reflecting the broad minimum to maximum scale for the applicable location.

Schedule

The internship runs for 11–14 weeks during Summer 2027 (May – September). Candidates must be available for the full duration.