About
Cupertino, California, United States Software and Services The Graphics, Games & Machine learning (GGML) team is looking for a Machine Learning Test and Automation Engineer to help deliver next-generation Apple Intelligence SW features on both On-Device and Private Cloud Compute. In this role, you will work hand-in-hand with GGML software developers and cross-functional ML teams during all project phases, collaborating on feature definition, quality plan, and test development. We’re looking for someone who is excited to explore new ideas, challenge assumptions, and create innovative approaches to validating complex ML systems. You bring curiosity, creativity, and a passion for quality — and you’re energized by the opportunity to work on technologies that reach millions of users while preserving their privacy. Description
As an Automation Engineer, you will design and build scalable test solutions that validate both on-device and distributed Apple Intelligence inference. Your work will focus on ensuring the correctness, reliability, and performance of our inference runtime software. You will develop functional and performance tests that push our systems to their limits, helping us deliver fast, efficient, and trustworthy ML-based experiences across Apple’s ecosystem. Responsibilities
Build scalable test solutions for validating ML-based inferences on Apple's hardware Design and maintain CI/CD pipelines to accelerate presubmissions and improve integration speed Help define and enforce best practices for automated testing within a high-velocity ML development lifecycle Partner closely with cross-functional teams, including ML engineering, infrastructure, and Apple Services Engineering Team to identify gaps in coverage and streamline testing strategies Minimum Qualifications
4+ years of proven experience in Software Quality Assurance Proficiency in Swift or Python Familiarity with XCTests/Xcode Experience building scalable automated test frameworks and integrating them into CI/CD pipelines Creative and analytical problem solver with strong attention to detail; highly organized, self-driven, and motivated to deliver results Preferred Qualifications
Familiarity with machine learning frameworks like PyTorch Understanding of the complete model development lifecycle, including data preprocessing, model training, evaluation, deployment, and monitoring 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 $141,800 and $258,600, 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 . Apple accepts applications to this posting on an ongoing basis.
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Languages
- English
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