Software Engineer- Systems

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn't have imagined, and now, can't imagine living without. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do.

APPLE INC has the following available in San Diego, California. Provide design and operational support of multiple Cloud-based applications with an emphasis on deployment, security, scalability and reliability running on public and Apple infrastructure. Work with teams on the design, implementation, maintenance, and monitoring of infrastructure for internal and tentpole projects. Define automation and processes for orchestrating hardware in custom lab environments. Investigate, diagnose, and remediated issues with continuous build and test pipelines, coordinating with code owners on root cause analysis. Serve as a central point for cross-team coordination on infrastructure capabilities and policy. Identify and document playbooks for automating task activity in response to infrastructure incidents. Engage in capacity planning, application optimization, and right-sizing on an ongoing basis. Contribute to Python and/or Golang software development tools to improve infrastructure automation. Perform peer code-reviews to improve the quality of automation software development. Provide subject matter expertise for specialized infrastructure development, including but not limited to training and serving machine learning models on distribute platforms (e.g. Kubernetes). 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 - $210,100/yr and your base pay will depend on your skills, qualifications, experience, and location. \n\nPAY & BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: \nNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Master's degree or foreign equivalent in Computational Data Science, Computer and Information Technology or related field. \nExperience and/or education must include:\n\nDeveloping automation scripts and tools in Python or Golang for software development, infrastructure management, or data processing tasks.\nBuilding or maintaining CI/CD pipelines for automating build, test, and deployment processes for software and infrastructure.\nIntegrating automated testing frameworks (e.g., pytest or unittest) within CI/CD workflows to ensure code quality and reliability.\nWorking in Linux/Unix environments for scripting, automation, and troubleshooting of infrastructure and deployment issues.\nDeveloping, integrating, or maintaining relational or NoSQL databases systems.\nUsing Cloud platforms (e.g., AWS, Azure, or Google Cloud Platform) for provisioning resources or deploying applications and pipelines.\nUsing infrastructure-as-code tools (e.g., Terraform) to provision and manage Cloud resources.\nUsing containerization technologies (such as Docker or Kubernetes) to package and deploy software.\nDeveloping, deploying, or maintaining machine learning models or infrastructure responsible for model training, model versioning, and serving inference models in production or staging environments.\nImplementing version control best practices using Git for collaborative software development and automated workflow integration.

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