Senior Machine Learning Platform Engineer - Ai, Search & Knowledge

Apple Apple · Big Tech · Cupertino, CA +1 · Machine Learning and AI

Senior Machine Learning Platform Engineer at Apple, focused on building and scaling the AI, Search & Knowledge platform. This role involves creating seamless integrations between ML frameworks and the platform, designing Python SDKs and APIs, and building backend services to support model management and serving infrastructure. The goal is to enable ML practitioners to focus on innovation by abstracting infrastructure complexity.

What you'd actually do

  1. create seamless integrations between our AI, Search & Knowledge platform and the diverse ML frameworks used across Apple, including PyTorch, JAX, and beyond.
  2. design Python SDKs and platform integrations that make it effortless for ML practitioners to move between datasets, training, model serving, and evaluation.
  3. build and scale core platform capabilities for model management and serving infrastructure while creating seamless integrations with the ML frameworks that Apple's teams depend on.
  4. design and build systems that feel native to each framework while providing a unified experience across the platform.
  5. build backend services, designing Python SDKs and APIs, creating integrations across ML tools and frameworks, and solving complex technical challenges that span multiple systems.

Skills

Required

  • Python
  • backend development
  • platform engineering
  • SDK design
  • API design
  • ML frameworks integration (PyTorch, TensorFlow, JAX, HuggingFace)
  • production-grade backend services (REST/GraphQL APIs, microservices, databases)
  • cross-functional collaboration
  • communication skills
  • cloud platforms (AWS, GCP, Azure)
  • Kubernetes

Nice to have

  • model serving systems (vLLM, Ray Serve, TorchServe, TensorRT)
  • inference optimization
  • open-source ML frameworks contributions
  • distributed training
  • model parallelism
  • large-scale ML workflows
  • MLOps practices
  • model management
  • experiment tracking systems

What the JD emphasized

  • 10+ years of software engineering experience with strong backend development skills and platform engineering mindset
  • Deep proficiency in Python with proven experience designing SDKs, libraries, and APIs for technical users
  • Experience integrating with complex ML frameworks (PyTorch, TensorFlow, JAX, HuggingFace) and building production-grade backend services (REST/GraphQL APIs, microservices, databases)
  • Track record of building end-to-end workflows that span multiple systems and teams, navigating complex technical landscapes to deliver pragmatic solutions
  • Strong cross-functional collaboration and communication skills to understand diverse stakeholder needs, technical requirements, and articulate design decisions across ML engineering, infrastructure, and product teams

Other signals

  • enables teams building Apple Intelligence
  • build and scale core platform capabilities for model management and serving infrastructure
  • seamless integrations with the ML frameworks
  • production-grade backend services
  • MLOps practices