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Software Engineer Simulation Infrastructure

Apple
Cupertino, USA
Full-time
Mid
Onsite
Discovered 1 months ago
PythonFastAPIFlaskPostgresReactKubernetes

Full Job Posting

Description

Our team develops a platform for running large-scale integration tests in simulation, using both virtual devices and physical hardware. You will help develop multiple aspects of this tooling including the launcher, runtime, frontend, backend and database. This team has a strong focus on efficiency and quality, ensuring that this system delivers results promptly without sacrificing correctness. Our ideal team member is highly motivated to pursue improvements and able to drive them to completion.

Minimum Qualifications

  • Strong software engineering fundamentals and deep proficiency in Python
  • Experience building and deploying HTTP services (FastAPI, Flask, or similar) and working with relational databases (Postgres or similar)
  • Experience with frontend technologies such as React or a comparable framework
  • Hands-on experience with cloud infrastructure: containers and Kubernetes, object storage, and managed compute
  • Solid command of networking and remote-execution fundamentals: TCP/IP, HTTP, WebSockets, SSH, and file transfer over the network
  • Comfort debugging across layers, from a failing test in a web UI down through a service, a VM, and the operating system it runs on
  • Strong operating systems background on Linux, macOS, or a comparable platform
  • BS/MS/PhD in Computer Science or a related field, or equivalent experience

Preferred Qualifications

  • Experience with virtualization and managing fleets of virtual or physical machines as a shared resource
  • Experience building test infrastructure, CI/CD systems, or developer tooling at scale
  • Working knowledge of a systems language such as Swift or C++
  • Familiarity with Apple platforms
  • Experience with authentication and authorization in production systems (OIDC/OAuth, certificate-based auth) and a working understanding of applied cryptography
  • Experience serving or evaluating machine learning models in production

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