Machine Learning & Artificial Intelligence Engineering Internship – Summer 2027

Role Overview

Potential Work

• Help build solutions and tools for next-generation mobile and embedded machine learning platforms.
• Contribute to AI systems infrastructure, distributed inference, compiler technologies, runtime systems, GPU acceleration, model serving, and ML workload deployment.
• Design, develop, and test software for ML tools and frameworks that improve model efficiency on edge devices.
• Collaborate with multidisciplinary research and internal engineering teams.

Minimum Qualifications

• Currently enrolled in a bachelor's, master's, or Ph.D. program in computer engineering, computer science, electrical engineering, or a related field.
• Available for 11-14 weeks during Summer 2027, between May and September.
• Expected graduation date of November 2027 or later.
• At least one year of experience with C, C++, Python, or similar programming languages.

Preferred Qualifications

• Graduate-level enrollment in a relevant engineering or computer science program.
• Experience with deep neural networks, machine learning algorithms, CNNs, RNNs, LSTMs, TensorFlow, TFLite, or PyTorch.
• Knowledge of compiler frameworks, parallel computing, AI infrastructure, inference systems, distributed computing, runtime systems, GPU programming, CUDA, Kubernetes, or MLIR.
• Knowledge of model compression, quantization, optimization, reinforcement learning, neural architecture search, or kernel optimization.
• Familiarity with on-device training, transfer learning, federated learning, NLP, ML security and privacy, generative models, audio or speech processing, computer vision, or wireless communication.
• Background in ML data pipelines, data management, application development, research publications, or object-oriented software design.

Internship Program

• Interns receive mentorship, manager support, professional development workshops, social events, cross-functional speaker sessions, and an executive speaker series.
• The program states that interns receive competitive hourly pay, accrued vacation time, relocation coverage, and furnished housing for the internship duration.

Potential Locations

• Internship opportunities may be available in Austin, Boulder, Boxborough, Bridgewater, Chandler, Irvine, New York City, Louisville, Raleigh, San Diego, Santa Clara, and Seattle, depending on team and project needs.

Application Process

• Applications are reviewed on an ongoing basis and candidates may be aligned to projects within the Machine Learning and AI Engineering track.
• The posting states that it is not a job posting for a specific project; advancing candidates may be invited to complete a timed HackerRank challenge.