AI Machine Learning Engineer II (Intern) - United States

Please note this posting is to advertise potential job opportunities. This exact role may not be open today but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens. Applications are accepted until further notice. Meet the Team Join our innovative engineering team focused on building next-generation AI/ML solutions. You’ll collaborate with skilled colleagues across platform, security, release engineering, and support teams to deliver high-impact products and ensure their perfect operation. Your Impact Dive into the development and implementation of cutting-edge generative AI applications using the latest large language models—think GPT-4, Claude, Llama, and beyond! Take on the challenge of optimizing neural networks for natural language processing and machine perception, drawing on a toolkit that includes convolutional and transformer-based models, student-teacher frameworks, distillation, and generative adversarial networks (GANs). Performance, scalability, and reliability are front and center as models are trained, fine-tuned, and put through their paces for real-world deployment. Collaboration is at the heart of this role—work alongside talented engineers and cross-functional teams to gather and prep data, design custom layers, and automate model deployment. Experimentation with new technologies and ongoing learning are always encouraged. Production-ready code, robust testing, and creative problem-solving all play a part in bringing innovative AI solutions to life. What an exciting place to grow and make an impact! Minimum Qualifications Currently enrolled in an undergraduate degree program with 2 years of relevant experience, or currently enrolled in a graduate degree program with 0 years of relevant experience. Relevant fields include: Computer Science, Electrical Engineering, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Software Engineering, or a related program. Backend development skills in Go or Python, demonstrated through a technical assessment, coding challenge, or code sample. Understanding of LLM infrastructure and optimization strategies, shown in a technical interview, assessment, or supporting documentation. Practical experience with model building and AI or LLM tasks, evidenced by a portfolio, code samples, technical evaluation, or academic/research project documentation. Preferred Qualifications Experience with inference engines such as vLLM, Triton, or TorchServe. Knowledge of GPU architecture, optimization techniques, distributed systems, and asynchronous programming models. Familiarity with agent frameworks and cloud-native platforms. Experience with cybersecurity principles and Python programming, including common AI libraries. Exposure to scalable computing environments and best practices for secure, efficient AI deployment. ProductIntern26 Why Cisco? At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. We are Cisco, and our power starts with you. Message to applicants applying to work in the U.S. and/or Canada: Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/ ... (truncated, view full listing at source)