Senior Software Engineer, Machine Learning Infrastructure and Quality

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Senior Software Engineer, Machine Learning Infrastructure and Quality

Apple

Location

Seattle, Washington, 98117, United States

Experience

Senior

Posted

Jul 22, 2026

Apply by

August 21, 2026

Applicants

0

Early applicantEasy applyFull-timeWork from Office

Job Description

The cloudOS team is responsible for all facets of delivering OS and system services on Apple silicon servers, including driving hardware and software initiatives to enable new Apple silicon-based systems in data centers. Our Apple Services Engineering team is hiring for an exciting new role as a Senior Software Engineer in Machine learning. We are seeking a highly motivated and detail oriented software engineer to drive innovations in software development and quality for various machine learning workflows. The right candidate for this position is passionate about delivering the best possible experience for our users and is continuously looking for new ways to measure and improve the quality of our software stack and infrastructure. Additionally, having the ability to switch between designing creative product usage scenarios and immersive analysis of detailed feature design will be a critical skill to possess. ## Description This is a full time Software Developer position where you will be driving working on various aspects of machine learning including training, inference, and characterization for various ML workloads. You will also be responsible to define, measure, and improve the quality of machine learning technologies at Apple by developing infrastructure, automation and services which facilitate validation and qualification of these technologies. In addition, you will be responsible for developing and implementing comprehensive automated test plans. You will be working cross-functionally with many teams across Apple impacting all levels of the Apple’s machine learning stack. You will be the voice of our customers, championing quality software development through each step of the development process and driving quality improvements throughout the organization. ## Minimum qualifications 5+ years of experience with hardware and/or software development lifecycle processes 5+years of experience in one or more compiled languages (e.g. C, C++, Objective-C/Swift) Proficient in one or more scripting languages e.g. Python, Go, or JavaScript Experience with Machine Learning, its common practical applications, and commonly used frameworks Proven understanding of Operating System concepts Proven ability crafting, maintaining and implementing tests plans across all application layers Applying statistical concepts to validate and QA data and models QA and automation experience involving ML workflows is a huge plus Posses the capability to accept ambiguity and deliver extraordinary results on tight schedules B.S., M.S., or Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or equivalent experience ## Preferred qualifications 5+years using one of the following scripting languages e.g. Python, Go, or JavaScript 5+years of experience working with an building Operating Systems

Key Responsibilities

  • Drive innovations in software development and quality for various machine learning workflows
  • Define, measure, and improve the quality of machine learning technologies
  • Develop infrastructure, automation, and services to facilitate validation and qualification of ML technologies
  • Develop and implement comprehensive automated test plans
  • Work cross-functionally with teams across Apple to impact the machine learning stack
  • Champion quality software development and drive quality improvements throughout the organization

Requirements

  • B.S.
  • M.S.
  • or Ph.D. in Computer Engineering
  • Electrical Engineering
  • Computer Science
  • or equivalent experience

Skills Required

CC++Objective-CSwiftPythonGoJavaScriptMachine LearningOperating System conceptsTest planningStatistical conceptsQAAutomationDetail orientedAbility to switch between designing creative product usage scenarios and immersive analysis of detailed feature designAbility to accept ambiguityDeliver extraordinary results on tight schedulesOperating Systems

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