Machine Learning Resource Management Engineer - SIML, ISE

Do you think Computer Vision and Machine Learning can change the world? Do you think it can transform the way millions of people collect, discover and share the most special moments of their lives? We truly believe it can. And we are looking for hardworking engineers who can contribute to building the ecosystem of tooling necessary to create these exciting technologies. We are the System Intelligent and Machine Learning (SIML) group that provides foundational computer vision and machine learning technologies to Apple’s ecosystem. Our work is behind essential features such as Camera, Text & Handwriting recognition, and Apple Intelligence experiences (Image Playground, Writing Tools, Smart Script, Math Notes). This is an exciting time to join us: grow fast, and have an impact on multiple key features on your first day at Apple!DescriptionOur team focuses on building the best possible ecosystem for ML R&D engineers to build Apple-quality ML-based technologies. We develop numerous tools to facilitate the development of ML models and collaboration around these ML models, and we manage the use of multiple resources such as training compute for Software Engineering or disk footprint of on-device ML models throughout our operating systems. This unique combination of tooling and resource management provides fantastic opportunities to improve the tools at the service of the policy efforts. These efforts cross organizational boundaries and impact almost every engineering organization within the company. In this role, you will focus on the resource management role of our team. You will be tasked to co-design, together with a senior architect, the next waves of improvements on how we manage these resources from a technical and policy standpoint, and how we influence the rest of the company on these aspects. It is a highly cross-functional role with significant exposure to challenges across all aspects of the stack.Minimum QualificationsBachelors or Masters degree in Computer Science, or equivalent experienceCapacity to design and lead infrastructure strategy and projects that guarantee a high level of service in a context of growing and evolving ML needs (storage, computation, networking, benchmarking...)Preferred QualificationsExcellent communication and interpersonal skillsProven organizational skills in order to establish durable processesExperience in software automationExperience in web developmentFamiliarity with machine learningDeep curiosity in what ML workloads and ML models do, in order to be able to assess them and the associated resource requirementsAt 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 $175,800 and $312,200, 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 take affirmative action to ensure 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.

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