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ross Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence. Our group is looking for an ML Infrastructure Engineer, with a focus on ML Performance Visualization. The role entails scaling and extending a significant on-device ML benchmarking service used across Apple.
Description
We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple's vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis. This role provides a great opportunity to help scale and extend a significant on-device ML benchmarking service used across Apple, in support of a range of devices from small wearables up to the largest Apple Silicon Macs. The role contributes to building the first end-to-end developer experience for ML development that, by taking advantage of Apple's vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis. The role further offers a learning platform to dig into the latest research about on-device machine learning, an exciting ML frontier! Possible example areas include model visualization, efficient inference algorithms, model compression, and/or ML compilers/run-time. Key responsibilities: * Drive UI/front-end experiences for a ML benchmarking service in a fast-paced environment * Explore intelligent visualization and insights of on-device ML models * Play a key role in maintaining the health and performance of the ML benchmarking service, including debugging failures and addressing user questions / requests. * Collaborate extensively with ML and hardware teams across Apple.
Minimum Qualifications
Experience with full-stack web development (e.g. Django) and front-end JavaScript frameworks (e.g. Vue or other comparable frameworks such as React or Angular).
Strong programming and software design skills in Python.
Knowledge of ML fundamentals including training regimes, evaluation and deployment/inference.
A passion/interest for ML, particularly applied to on-device use cases.
Excellent collaboration and communication skills.
Preferred Qualifications
Masters or PhDs in Computer Science or relevant disciplines.
Experience with any ML authoring framework (PyTorch, TensorFlow, JAX, etc.) is a strong plus, particularly on-device ML frameworks such as CoreML, TFLite or ExecuTorch.
Back-end system skills including containers (docker), cloud orchestration (Kubernetes), database (SQL, Postgres)
Experience with standard ML architectures such as Transformers, CNNs or Stable Diffusion a strong plus.
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 $139,500 and $258,100, 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 .
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