Sr. Software Engineer (distributed System)

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

Build and operate a distributed crawl platform that fetches, renders, and extracts structured knowledge from billions of web pages to power Siri, Apple Intelligence, Spotlight, and Apple Maps. This role focuses on a large-scale, production system with strict latency SLOs and high operational stakes, leveraging modern AI coding tools.

What you'd actually do

  1. help build and operate a distributed crawl platform
  2. continuously fetches, renders, and extracts structured knowledge from billions of web pages
  3. own the critical components of the systems and will be responsible for shaping the roadmap
  4. work across the full crawl lifecycle, from how requests are scheduled and dispatched, to how pages are fetched and rendered, to how structured data is extracted and delivered downstream

Skills

Required

  • 5+ years or experience building scalable distributed systems at scale
  • Strong understanding of data structures and algorithms
  • Strong systems programming background — Rust, Scala, or Go
  • Solid understanding of async programming models, queue-based architectures, and at-least-once / exactly-once delivery semantics
  • Deep expertise of Cloud infrastructure deployments, managing workloads across heterogeneous clusters (EKS and/or bare-metal)
  • Hands-on Kubernetes experience — multi-cluster, resource tuning, HPA, rolling deployment
  • Hands-on AWS experience: SQS, S3, MSK (Kafka), EKS, IAM, VPC, Transit Gateways
  • Familiarity with Kafka — topic management, consumer group lag, partition rebalancing
  • Experience defining metrics, writing alert rules, and building dashboards for distributed services
  • Excellent interpersonal skills able to work independently as well as cross-functionally
  • BS or MS in Computer Science or equivalent experience

Nice to have

  • Experience in Web Crawl is a plus
  • Headless browser infrastructure at scale is a plus
  • Flink or Spark streaming/batch pipelines over Iceberg is a plus

What the JD emphasized

  • strict latency SLOs
  • high operational stakes