Performance & Capacity Engineer, Infrastructure Services

Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world? Join Apple's Information Systems and Technology (IS&T) organization.

IS&T is the engine behind everything Apple does for customers and for the people who build for them. It's Apple's central nervous system. Supporting 2.5 billion active Apple devices, processing billions of secure transactions, and keeping the technology that defines modern life running flawlessly, IS&T makes the impossible feel effortless."

Do you love building solutions to handle global complexity and immense scale? Imagine what you could do here.

Infrastructure Services is part of IS&T and the foundation of Apples global network operations - managing data center equipment and systems to deliver compute, storage, and networking services for teams across Apple, including its internal developer community. From individual facilities to a worldwide network, Infrastructure Services ensures the technology underneath everything works without question.

We are seeking a highly motivated Performance & Capacity Engineer to join our global network infrastructure team to develop intelligent analytical tools, predictive models, and data-driven solutions. Here, you will bring your unique perspective, collaborate across disciplines to do the best work of your life, and deliver transformative tools that strengthen our core global network. If you are a motivated self-starter who thrives in a fast-paced environment and wants to bridge the gap between AI, data science, and scalable network infrastructure, this team is the right place for you. As a member of our global network infrastructure team, you will develop data-driven solutions to support capacity planning, traffic forecasting, and performance optimization across Apples Core Backbone and Internet Edge network. Collaborating closely with network architecture and engineering teams, you will analyze large-scale network telemetry and performance datasets to uncover traffic patterns, identify trends, and generate actionable insights.

In this role, you will apply mathematical modeling, statistical analysis, simulation, and predictive analytics to forecast network capacity requirements, evaluate infrastructure demands, and solve complex network planning and optimization problems. You will design intuitive data visualizations and interactive dashboards to communicate analytical findings and support data-driven engineering decisions. You will also explore AI/ML techniques to enhance forecasting accuracy, identify anomalies, and automate analytical insights.

If you are passionate about data science, mathematical problem-solving, and applying analytics to complex real-world infrastructure challenges at scale, this team is the right place for you. Develop mathematical, statistical, or data-driven models to support capacity planning, demand forecasting, and routing optimization. Run scenario analysis - traffic growth, link failures, planned upgrades - to test whether the network can carry forecast demand. Analyze large-scale network telemetry and performance datasets to identify traffic patterns, utilization trends, anomalies, and potential capacity constraints. Design and develop interactive dashboards and data visualizations to communicate network performance, traffic trends, and forecasting insights. Leverage modern developer tools, automation, and AI-assisted workflows to enhance data analysis, forecasting, and network capacity planning. Develop scalable data processing pipelines to collect, transform, and analyze large-scale network telemetry and performance datasets. Apply AI/ML techniques and statistical analysis to uncover operational insights and automate anomaly detection.Bachelor's in Computer Science, Data Science or equivalent practical experience. Experience in software development, applied data science, data engineering, or equivalent hands-on project experience. Experience with mathematical modeling, forecasting, regression analysis, or time-series modeling. Proficiency in Python or a similar programming language for data analysis, mathematical modeling, and developing analytical tools. Hands-on experience working with relational or non-relational databases (e.g., PostgreSQL, MySQL, NoSQL, or time-series stores). Experience developing data visualizations, dashboards, or analytical reporting tools. Has built and deployed at least one web application or internal tool end to end (for example, Flask or FastAPI with React, Dash, Streamlit, or similar).Master's in Computer Science or equivalent practical experience. Foundational understanding of network concepts: TCP/IP stack, IP routing basics, or network telemetry (Flow data, telemetry streams). Familiarity with Linux/Unix environments, containerization (Docker, Kubernetes), and CI/CD pipelines. Experience with data analysis libraries (Pandas, NumPy, SciPy, statsmodels, Scikit-Learn).