Description

Description

In this role, you will develop methods to improve and automate the collection, storage, processing, and visualization of silicon validation data from labs worldwide. You'll build and deploy scalable data pipelines using scheduling systems and design infrastructure to support distributed validation across bare metal macOS, Docker, and Kubernetes environments. You will also automate the setup of silicon validation environments and manage data migration across systems. A part of the role includes instrument tracking and network automation-integrating with lab hardware to configure devices, manage network environments, monitor instrument status, and collect validation data securely and at scale. For efficient and insightful data analytics, you'll build AI/ML based tools that accelerate data analysis and integrate with existing data analysis platforms. This includes tracking power utilization of lab equipment, identifying patterns in usage, and optimizing for future demand through predictive modeling. This work involves close collaboration with hardware, software, and infrastructure teams to enable rapid data exploration, debug large-scale systems, and implement alerting mechanisms that enhance observability and transparency across automation workflows.

Minimum Qualifications

• BS and 3+ years of relevant industry experience.

Preferred Qualifications

• Proficiency in Python and best practices for automation and tooling.
• Experience building and maintaining CLIs, APIs, and end-to-end data pipelines using schedulers and orchestration tools.
• Familiarity with databases (SQL/NoSQL), file systems, and object storage.
• Hands-on experience with Docker, Kubernetes, CI/CD pipelines and version control systems.
• Proven track record to debug, deploy and support distributed systems in production.
• Experience automating network configuration and diagnostics to streamline lab setup and improve reliability.
• Experience designing secure data infrastructure with authentication, RBAC, and environment isolation.
• Proven collaborator across teams, emphasizing clarity, ownership, and timely communication.
• Experience working with scalable object storage and distributed file systems in cloud environments.
• Experience developing, deploying, and maintaining applied ML or statistical modeling pipelines to analyze lab and system data at scale.
• Experience implementing alerting and monitoring systems for workflow health and failure detection.

Pay & Benefits

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 $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.

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.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .