Senior Full-Stack Engineer - Web Platforms for ML Inference

Apple's AIML organization powers intelligence across many of our most iconic experiences. Within AIML, the Annotation AI Services organization builds the foundational systems that enable large-scale model inference, data pipelines, and ML platform capabilities for annotation platforms.\\n\\nWe are looking for a Senior Full-Stack Engineer who enjoys working across modern web applications and cloud-native backend systems. This role is ideal for engineers who value end-to-end ownership-from designing polished, scalable React + TypeScript web platforms to building and operating the cloud infrastructure and services that power them.\\n\\nYou will focus on web platforms used by annotation platforms and operation teams across Apple to discover, configure, and interact with inference services, pipelines, and ML infrastructure-helping make complex systems accessible, reliable, and scalable.

As a Senior Full-Stack Engineer on the Annotation AI Services team, you will design and build web platforms that sit at the front door of ML inference and pipeline systems.\n\nYou will create modern, high-quality React and TypeScript applications while also developing cloud-native backend services deployed on AWS and Kubernetes. The role values engineers who appreciate working across the stack and who enjoy collaborating closely with infrastructure, ML systems, and platform teams to deliver cohesive, end-to-end solutions.

5+ years of professional software engineering experience.\nStrong experience building and shipping production web applications with React and TypeScript (including testing and performance).\nWorking backend experience with Python and/or Node.js building APIs and integrations used by frontend applications.\nExperience shipping and debugging services in a cloud environment (AWS preferred) and a containerized runtime (Kubernetes/EKS or equivalent preferred).\nExperience designing and consuming APIs for frontend-backend integration (REST and/or gRPC), including auth, pagination, and error handling.\nSolid fundamentals in web architecture and security (authentication/authorization and secure API design).\nComfortable working across the stack and collaborating with product/design/backend/infrastructure partners.\nBS in Computer Science or equivalent practical experience.

Experience building internal platforms or developer-facing tools.\nFamiliarity with ML platforms, inference systems, or data pipelines.\nExperience with gRPC and/or Protobuf-based APIs.\nExposure to observability systems (metrics, logging, tracing).\nExperience operating services in production Kubernetes environments.\nExperience with safe rollout strategies (e.g., canary or blue/green), autoscaling, and Kubernetes resource tuning (requests/limits).\nExperience with performance and cost optimization: load/perf testing, caching strategies, capacity planning, and rate limiting/quotas.\nExperience designing/operating persistence and messaging patterns (e.g., DB + queues + object storage), including schema migrations and reliability patterns (retries/DLQs).\nMS in Computer Science or related field.