Sr. AI Inference Platform Engineer

Apple • Seattle, WA

9d

About The Position

Apple is seeking a senior engineer to build tooling, automation, and analysis capabilities for its AI inference platform. The role focuses on performance benchmarking systems, capacity projection models, and data analysis pipelines that inform infrastructure teams and capacity planners. Working across AI systems performance, distributed infrastructure, and software engineering, the engineer will help teams make data-driven decisions about scaling and optimizing inference infrastructure.

As part of the next-generation datacenter engineering team, the engineer will build tools and analysis systems that provide visibility into performance across the fleet. The work will influence hardware investment, production regression detection, and capacity forecasting. This is a high-impact, cross-functional position focused on turning complex data into actionable insight at large scale.

Requirements

• Bachelor’s or master’s degree in Computer Science or a related technical field.
• Solid understanding of AI/ML inference architecture and the performance characteristics of serving systems.
• Seven or more years of experience in performance and infrastructure engineering in distributed systems.
• Seven years of experience coding in Python, Go, C++, or other programming languages.
• Experience with automation engineering, tooling, and data pipelines supporting 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.

Nice To Haves

• 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, such as Nsight or other vendor-specific profilers.
• Experience with data visualization and reporting tools or frameworks for surfacing performance trends to stakeholders.
• Familiarity with ML serving frameworks and runtimes, such as Triton, TensorRT-LLM, vLLM, or similar.
• Experience with CI/CD and workflow orchestration tools for building automated performance analysis pipelines.
• Knowledge of cluster schedulers and orchestration platforms, such as Kubernetes.
• Experience with metrics and logging tools, such as Prometheus, Grafana, or Splunk.

Responsibilities

• Design and build automation to evaluate AI inference performance across hardware generations and configurations.
• Develop tools that surface performance trends, regressions, and insights to infrastructure and planning teams.
• Build projection and forecasting models to support long-term capacity planning decisions.
• Analyze performance and utilization data to identify bottlenecks, trends, and optimization opportunities.
• Partner with AI infrastructure engineers, hardware teams, and capacity planners to deliver data and tooling.
• Create and enhance performance analysis workflows to increase team velocity and data reliability.
• Continuously improve the accuracy, coverage, and usability of performance measurement and analysis systems.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior