Software Engineer

In this highly collaborative role, you will be at the center of multiple efforts to utilize hardware acceleration for machine learning and high performance computing workloads. You will be part of a team that builds and maintains system software such as runtime libraries, frameworks, and daemons that will power the next generations of data centers. You will partner with teams across Apple to adapt, tailor, and scale software on a novel compute platform and will help to build the foundation of our future cloud architecture. We are looking for someone with proven mastery building and managing scalable, resilient systems.

You should have a strong mix of education and practical experience with a real passion for diving head first into challenging problems. Description We are seeking a skilled Software Engineer to join our System Software Team focused on optimizing and maintaining the core infrastructure of our data center environments. You will work on enhancing operating system performance, scalability, and reliability, ensuring seamless operations for large-scale distributed systems. Minimum Qualifications + 4+ years of software engineering experience. + Bachelors or Masters in Computer Science, Computer Engineering, or equivalent experience. + Demonstrated innovative and creative thinking capabilities. + Proficiency in one of C/C++, Obj-C, Swift. + Strong knowledge of OS architecture, and low-level system components. + Passion for software architecture, APIs, and high performance extensible software. + Excellent communication skills. + Creative, collaborative, and product-focused. + Solid understanding of Linux or Apple OS system programming, including process management, IPC, signals, and daemon lifecycle. Preferred Qualifications + Familiarity with init systems (systemd, launchd, upstart) and service orchestration. + Knowledge of distributed systems, cloud computing, and large-scale data center infrastructure is a plus. + Experience with Swift, Objective-C and Apple development tools. + Experience with AI accelerators (GPUs, TPUs, ASICs) or distributed systems. + Knowledge of cloud technologies (Docker, Kubernetes) and AI workload orchestration.