We are seeking an engineer to enhance our AI inference platform through tooling, automation, and analysis capabilities. This role involves developing performance benchmarking systems, capacity projection models, and data analysis pipelines that support our AI infrastructure teams. You will work at the intersection of AI systems performance and software engineering, helping the team make informed decisions about scaling and optimizing our platform. This position is part of our next-generation datacenter engineering team and focuses on providing real-time insights into performance across our infrastructure.

• BS or MS in Computer Science or a related technical field.
• Solid understanding of AI/ML inference architecture and performance characteristics of serving systems.
• Experience with performance and infrastructure engineering in distributed systems.
• Proficiency in Python, Go, C++, or other programming languages.
• Experience with automation engineering, tooling, and data pipelines to support engineering workflows.
• Strong knowledge of GPU/accelerator architecture as it relates to AI workloads.
• Practical statistical knowledge applicable to performance analysis and forecasting.
• Excellent communication skills and ability to turn data into clear guidance for infrastructure teams and capacity planners.
• Experience with performance benchmarking and methodologies for AI/ML inference systems.
• Familiarity with capacity planning and forecasting/projection models for large-scale infrastructure.
• Experience with GPU profiling and observability tools.
• Experience with data visualization and reporting tools/frameworks for surfacing performance trends to stakeholders.
• Familiarity with ML serving frameworks and runtimes.
• Experience with CI/CD and workflow orchestration tools for building automated performance analysis pipelines.
• Knowledge of cluster schedulers and orchestration platforms.
• Experience with metrics and logging tools.

• Design and build tooling and analysis systems for AI infrastructure.
• Provide real-time performance insights to engineers and capacity planners.
• Influence hardware investment decisions based on performance data.
• Detect regressions before they reach production through effective monitoring.
• Forecast capacity needs months in advance to ensure scalability.
• Turn raw data into actionable insights for the team.
• Collaborate with cross-functional teams to optimize the inference platform.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.