About The Position

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. Manufacturing Systems and Infrastructure (MSI) team is an engineering organisation under the Product Operations org. MSI is responsible for the design, development and maintenance of system tools, services and applications required to efficiently run manufacturing operations at scale across global factory sites. As a Wireless Systems Automation Engineer with the MSI team, you will serve as the regional engineering lead for wireless technologies, AI-assisted automation and edge computing on the factory floor. You will use Generative AI coding assistants to rapidly develop and deploy robust automation solutions, design and scale machine learning pipelines directly onto manufacturing lines and deploy edge computing hardware optimised for real-time, local AI inference. You will own critical new line bring-ups (NPI) end-to-end - from system architecture and test infrastructure through AI model deployment - while providing hands-on engineering support to resolve line-blocking issues at regional factory sites.

Requirements

  • 5+ years of experience in object-oriented programming language(s)
  • Strong proficiency in Python (specifically for ML/AI integration), Embedded C/C++, Perl, Ruby, and Shell Scripting (Bash)
  • Hands-on experience utilising recent Generative AI tools and coding assistants (e.g., GitHub Copilot, ChatGPT) to accelerate script development, refactor code, and automate technical workflows
  • Proven track record of delivering complex systems, applying modern AI-assisted workflows to accelerate development lifecycles
  • Deep understanding of IoT messaging (MQTT, CoAP) and standard network/web protocols (TCP/IP, HTTP) to facilitate data pipelines for AI inference
  • Expertise in Bluetooth and NFC for modern factory connectivity
  • Experience bridging modern system with legacy industrial hardware using serial communications (RS232, UART)
  • Skilled in firmware development, debugging, cross-compilation, and flash programming for edge computing devices
  • Ability and willingness to travel up to 30% (domestic and international)
  • Bachelors / Masters in Computer Science or related fields
  • Strong grasp of security principles and best practices, particularly securing edge devices and data streams in an industrial IoT setting
  • Experience integrating systems with peripheral interfaces, supported by a foundational knowledge of basic electronics
  • Strong background in robotics and manufacturing automation, with the ability to deploy AI-driven systems onto physical factory equipment
  • Excellent communication skills — ability to articulate technical trade-offs clearly to both engineering teams and non-technical manufacturing stakeholders
  • Adept at managing project scope and timelines, utilising AI productivity tools to optimise planning and resource allocation
  • Proven ability to act as the technical bridge between QA, Hardware, Operations, and Product teams to ensure seamless manufacturing systems integration
  • Experience in performance management and team development, fostering a culture that embraces new technologies and AI adoption
  • Self-motivated with an entrepreneurial spirit, excellent time management, and the strong written/verbal communication skills necessary to explain complex technical trade-offs
  • Experience in manufacturing, factory automation, or industrial IoT systesms

Responsibilities

  • Utilise AI coding assistants (e.g., GitHub Copilot, Cursor) to rapidly develop and deploy robust automation solutions and wireless technologies within the factory environment.
  • Design, integrate, and scale machine learning pipelines and wireless applications directly to the factory floor, leveraging GenAI tools to continuously optimise test sequences, automate fault detection, and drive operational efficiencies.
  • Design and deploy edge computing hardware (such as Mac mini fleets) optimised for local AI inference, ensuring real-time data processing on the manufacturing lines.
  • Serve as the primary regional engineering lead for establishing system architecture, test infrastructure, and AI model deployment pipelines during new manufacturing line bring-ups (NPI).
  • Debug intricate integration issues between system applications, AI inference engines, edge hardware, the factory network, and physical test fixtures during the initial line ramp-up phase.
  • Provide rapid, hands-on engineering support at regional factory sites to resolve critical line-blocking issues, utilising advanced data analytics and GenAI-powered diagnostic tools to accelerate root-cause analysis.
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