Software Engineer Data & AI I (Intern) - United States

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About the role

Cisco Product Internship Program The Cisco Product Organization is the engine behind the platforms, technologies, and solutions defining the next generation of connectivity. Spanning AI Software & Platforms, Core Product Engineering, Collaboration, Security, Networking, Silicon, and Observability, we build the critical infrastructure that powers the digital world. Millions of people rely on our platforms every day, and our teams work together to build, refine, and scale products that drive meaningful impact. We are a team of passionate innovators, united by our curiosity, collaboration, and dedication to helping one another do our best work. Ready to help us build what's next? The Cisco Product Internship Program offers a 12-week summer experience designed to welcome early-career talent into this mission. We embed interns within high-impact teams, where they collaborate directly on the products, platforms, and architectures shaping Cisco's future and powering the AI era. Throughout the program, interns have the opportunity to participate in targeted learning sessions, multi-functional networking, and direct engagement with leaders across the organization. By immersing interns in real-world challenges, we help them build the technical skills, confidence, and collaborative approach needed to envision a long-term, impactful career at Cisco.

Your Impact: You'll build data pipelines and machine learning workflows together, using Python to power real-world products. You'll develop, train, and deploy models using frameworks like PyTorch or scikit-learn, and orchestrate large-scale data solutions using tools like Spark and Kubernetes. By building and scaling the intelligent data pipelines and distributed systems that power our models, you ensure our platforms remain performant and reliable as we process data at scale to drive the insights that fuel our AI-driven products.

Minimum Qualifications: Currently enrolled in an undergraduate degree program (Associate's or Bachelor's).Qualifying education should be in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field. Expected to continue enrollment in degree program following completion of the internship. Proficient in Python and core data structures, demonstrated through at least one academic, personal, or professional project Exposure to at least one ML framework: Tensor Flow, PyTorch, or scikit-learn Working knowledge of at least one big data/distributed processing tool: Spark, Hadoop (Map Reduce), or Flink Hands-on experience with at least one deployment/orchestration tool: Docker or Kubernetes

Preferred Qualifications: Experience deploying or productionizing a trained ML model, beyond coursework-level training and evaluation Exposure to at least one cloud platform: AWS, Azure, or Google Cloud Understanding of at least two of: scalability, reliability, fault tolerance, or data consistency Working knowledge of at least two of: load balancing, consensus algorithms, or inter-service communication

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