ML Model Integration Platform Eng

Join the Apple Service Engineering (ASE) team and drive innovation that matters! The ASE team builds and provides systems and infrastructure that fuel Apples services. As part of this team you will be responsible for building and integrating technologies that enhance peoples lives. We are also tasked with enabling Apple Intelligence and Private Cloud Compute in the cloud. Were looking for a senior engineer who can help integrate Large Language Models into our software ecosystem.

This role is for a Platform Engineer specializing in Apple Intelligence and Private Cloud Compute. Your responsibilities will include architecting designing and delivering the systems and platform components that integrate Large Language Models (LLMs) and other AI models into Apples products. This role establishes the foundation that enables teams to safely and effectively deploy ML-powered features. You will ensure the systems surrounding the models are robust scalable and easy for others to build on becoming a key partner in the organizations delivery of AI-driven experiences. The ideal candidate is a systems thinker who can navigate fast moving requirements while maintaining a long-term vision for resilient and scalable solution.

Develop and maintain runtime services APIs tooling and automation for model consumption deployment versioning evaluation and internal tools (CLIs micro-services automation pipelines) to enhance developer architectural decisions for distributed systems involved in model serving prioritizing reliability throughput observability and cost cross-functionally with product infrastructure security and engineering teams to identify limitations create solutions and align on technical technical mentorship elevate engineering standards and lead initiatives that improve the platform as it and deliver platform components that integrate ML Models into our application as a systems thinker who can map how changes propagate across the platform guiding teams toward resilient and future-proof rapidly changing requirements and adapt plans swiftly without compromising long-term objectives.

5 years of software engineering experience in building and operating production background in distributed systems and an ability to reason about scale concurrency and failure experience designing and implementing internal tools automation and service-level to collaborate closely across teams and influence decisions through clarity empathy and technical holistic mindsetseeing beyond individual components to understand and communicate system-level working in dynamic fast-changing environments where you help create structure not wait for in scripting and programming languages such as C/C Python SQL ShellnBachelors degree in Computer Engineering Electrical Engineering Computer Science or related field

Understanding and practical experience with containerization technologies (Docker) and orchestration platforms (Kubernetes).nSolid background in one or more major cloud providers (AWS GCP Azure) including familiarity with compute storage networking and security services relevant to ML workloads.