Software Engineer Data​/AI​/Systems II; Intern

Meet the Team

Our dedicated team members are building the future of Cisco’s AI-driven platforms and data infrastructure, supporting innovation across the globe. You will join teams focused on developing advanced data pipelines, machine learning infrastructure, and analytics platforms within business groups such as S&TO, Supply Chain, and Infrastructure Engineering. As part of this collaborative environment, you will contribute to the growth of emerging technologies in data and intelligent systems.

Explore the opportunities at the intersection of data engineering and AI, helping to transform how Cisco and its customers harness information and intelligent automation.

You are a passionate software engineer with expertise in developing scalable data pipelines, designing robust analytics platforms, and building infrastructure to support machine learning initiatives. Your strong background in programming, data systems, and collaboration enables you to solve complex challenges with innovation and attention to detail. By building and maintaining key software tools and platforms, you enable Cisco’s business groups to leverage AI and data-driven insights for operational excellence and strategic growth.

Your work ensures high-quality, reliable data infrastructure that supports Cisco’s leadership in intelligent, scalable technology solutions.

• Currently enrolled in a certification program (e.g., Boot Camp, Apprenticeship, Community College or 4-Year University with 2 years of relevant experience) or currently enrolled in a graduate degree program with 0 years of relevant experience. Proficiency in Python, with a strong understanding of fundamental data structures.
• Hands‑on experience with machine learning frameworks such as Tensor Flow, PyTorch, or scikit‑learn.
• Familiarity with distributed data processing technologies, including Apache Spark, Hadoop (Map Reduce), or Apache Flink.
• Experience with containerization and orchestration tools, such as Docker and Kubernetes, for deploying data and machine learning workloads.

• Hands‑on experience with AI/ML.
• Familiarity with major cloud platforms, such as AWS, Azure, or Google Cloud.
• Understanding of distributed systems concepts, including scalability, reliability, fault tolerance, and data consistency, as well as familiarity with distributed computing patterns (e.g., load balancing, consensus algorithms, and inter‑service communication).