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Software Engineer - AiDP Reliability Engineering, IS&T, Early Career Opportunities
Apple, Inc.Austin, TX🇺🇸United StatesPosted 14 Aug 2026
Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
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.
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!
Description
We are looking for engineers who have strong coding skills and computer science foundation with passion for building resilient and highly performant distributed systems. 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. You will:
- Build, enhance, and maintain multi-tenant systems employing diverse technologies
- Collaborate with multi-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
We are looking for enthusiastic engineers with interest in one of the following areas:
- ML Engineers
- Big Data Engineer
- Platform Reliability Engineer
Minimum Qualifications
Bachelor's Degree in Computer Science, Computer Engineering or equivalent technical degree
Proficient programming knowledge in one of the following areas: Python, Java, or Go Programming and ability to read and explain open source codebase
Good foundation of Operating Systems, Networking and Security Principles
Relevant Internship experience
Preferred Qualifications
Excellent analytical & problem solving skills
Exposure to Model Training or Fine Tuning methodologies
Exposure to Spark/Flink/Trino/Iceberg and other modern cloud native big data technologies
Exposure to Kubernetes and other cloud native technologies like Flux/Argo CD
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!
Description
We are looking for engineers who have strong coding skills and computer science foundation with passion for building resilient and highly performant distributed systems. 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. You will:
- Build, enhance, and maintain multi-tenant systems employing diverse technologies
- Collaborate with multi-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
We are looking for enthusiastic engineers with interest in one of the following areas:
- ML Engineers
- Big Data Engineer
- Platform Reliability Engineer
Minimum Qualifications
Bachelor's Degree in Computer Science, Computer Engineering or equivalent technical degree
Proficient programming knowledge in one of the following areas: Python, Java, or Go Programming and ability to read and explain open source codebase
Good foundation of Operating Systems, Networking and Security Principles
Relevant Internship experience
Preferred Qualifications
Excellent analytical & problem solving skills
Exposure to Model Training or Fine Tuning methodologies
Exposure to Spark/Flink/Trino/Iceberg and other modern cloud native big data technologies
Exposure to Kubernetes and other cloud native technologies like Flux/Argo CD
Skills
Flink
Machine Learning
Go
Java
Kubernetes
Python
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