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Consumer Electronics, Software, Services, Retail

On-Device Machine Learning Engineer

Sunnyvale, California, United StatesOnsiteFull Time$181,100–$318,400 /yrPosted 27 days agoVisa sponsorship available

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Role summary

Apple is seeking a Machine Learning Integration Engineer for its Video Computer Vision team to deploy and optimize computer vision models on Apple devices. This role involves converting foundation models, evaluating their performance and efficiency on-device, and reducing inference latency. The ideal candidate will have a strong understanding of model compression techniques, operating systems, and programming in Python and C++, with experience in PyTorch and the ML development lifecycle. Preferred qualifications include experience with CoreML, Swift, and real-time video pipelines.

We’re starting to see the incredible potential of multimodal foundation and large language models, and many applications in the computer vision and machine learning domain that previously appeared infeasible are now within reach. We are looking for a highly motivated and skilled Machine Learning Integration Engineer to join our team in the Video Computer Vision group and help us ship cutting edge computer vision technology on Apple devices. The Video Computer Vision org has pioneered features such as FaceID, FaceKit, and Gaze and Hand gesture control which have changed the way millions of users interact with their devices. We balance research and product requirements to deliver Apple quality, pioneering experiences, innovating through the full stack, and partnering with HW, SW and AI teams to shape Apple's products and bring our vision to life.
Description
As part of the Video Computer Vision (VCV) team, you will deploy purpose-built vision models on Apple devices, developing innovative techniques to optimize their performance, efficiency, and scalability on-device.","responsibilities":"Convert and integrate foundation models for on-device deployment.
Evaluate power and performance of models running on Apple devices.
Optimize on-device inference latency and efficiency of CV/ML models.
Preferred Qualifications
Experience with CoreFoundation, RealityKit and CoreML frameworks.
Fundamental knowledge of real-time video pipelines, image transformations, and rendering loops.
Programming experience with Swift.
Minimum Qualifications
BS and a minimum of 10 years relevant industry experience.
Strong knowledge of model compression techniques such as pruning, distillation, quantization and weight clustering.
Solid understanding of operating system and extensive programming experience in Python and C++.
Experience working with PyTorch.
Experience with machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment.
Foundational understanding of machine learning: MultiModal LLMs and integration of ML components into production systems.
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 $181,100 and $318,400, 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.

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