Software Engineer, Reliability Engineering, AiDP

Apple·Austin, Texas, United States·posted 11d ago · last seen 2m ago

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About interviewing at Apple

One of tech's least standardized loops: you interview for a specific team, and every stage belongs to it. Recruiter/hiring-manager screen, one to three 45–60 minute Coderpad coding screens, a system design round shaped by Apple's reliability and privacy constraints, and a behavioral round — then a panel debrief. There is no central question bank; questions map to the team's real stack.

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Description

Summary

The Applied Machine Learning team in AI and Data Platform org has been at the forefront of accelerating digital transformation through machine learning across Apple's enterprise ecosystem. We build and operate ML, GenAI, Inference and Data Platforms and Services to provide a comprehensive suite of capabilities—serving business-critical needs across Apple's enterprise. We work on interesting and hard challenges related to scale and performance across diverse set of open-source and cutting edge technologies.

Description

We are looking for a talented engineer to join our team and bring passion for building and operating large scale platform and distributed systems leveraging cutting edge open source technologies across hybrid cloud environments.As a software engineer in AiDP reliability engineering you will work on one or many projects related to GenAI, ML, Inference and Big data platform.

Key Responsibilities

Build, enhance, and maintain multi-tenant systems leveraging diverse technologies. Collaborate with cross-functional teams to deliver impactful customer features. Lead projects through full lifecycle, from design discussions to release delivery. Operate, scale, and optimize high-throughput and highly concurrent services. Diagnose, resolve, and prevent production and operational challenges.

Minimum Qualifications

BS/MS in computer science or equivalent experience. 2+ years experience programming skills in one of the following areas: Python, Java, or Go. 2+ years experience in Kubernetes, Docker or other container orchestration framework.

Preferred Qualifications

Ability to read and explain open source codebase. Experience deploying and managing CI/CD pipelines. Strong expertise in troubleshooting complex production issues. Should be able to understand complex architectures and be comfortable working with multiple teams. Ability to conduct performance analysis and troubleshoot large scale distributed systems. Should be highly proactive with a keen focus on improving uptime/availability of our mission-critical services. Experience with big data technologies - Spark, Flink, Iceberg or emerging GenAI/ML like Ray/MLflow/model serving) technologies. Experience of Linux, database and security concepts.

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