
Machine Learning Engineer, Platform Architecture
Cupertino, CAJobSeen 2 days agoSeen in employer's feed 2 days ago
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Job overview
Apple’s Platform Architecture group connects hardware and software and works at the intersection of machine learning applications and Apple silicon architecture. The Machine Learning Engineer will map ML workloads to Apple silicon, develop performance models and simulations, and use performance studies to inform architecture decisions. The role collaborates with architecture, system, software, and algorithm teams to develop optimized solutions and analyze system architecture trade-offs.
Skills & qualifications
Skills
Qualifications
Full job description
Role Number: 200693487-0836
Summary
At Apple, our Platform Architecture group is responsible for connecting our hardware and software into one unified system. You’ll collaborate with engineers across Apple to design how our technologies work in unison, drive development of our renowned system-on-a-chip architecture and develop forward-looking prototype systems. Our team works at the intersection of ML applications and Apple silicon architecture. We collaborate with SoC/IP architecture, system, software, and algorithm teams to develop integrated, highly optimized solutions for machine learning applications.
In this role, you will explore different ways of mapping ML workloads to Apple silicon and develop performance models/simulations. Your work will inform and validate architecture decisions. You will gain insights on how to make workloads run efficiently on our SoCs and communicate what we learn to software and algorithm teams.
Description
Create optimized implementations of ML workloads on Apple silicon including Neural Engine, GPU, and CPU. Collaborate with IP and SoC architecture teams to develop performance models and simulations of future hardware. Conduct performance studies to inform and validate architecture decisions. Collaborate with system teams to create high-level performance models of emerging ML techniques and analyze system architecture trade-offs.
Minimum Qualifications
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Bachelor’s degree
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Programming experience in C/C++ and/or Python
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Experience in computer architecture
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Experience with at least one hardware IP: ML HW accelerators or processing units such as GPU, image/video, CPUs, or similar
Preferred Qualifications
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MS or PhD in EE/CE/CS or related field and 3+ years of relevant experience
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Experience with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms
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Experience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environments
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Experience designing experiments to evaluate ML model optimization techniques
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Experience in creating SoC or IP performance models/simulations
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Verbal and written communication skills for collaborating with partner teams
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Ability to prototype algorithms on CPU/GPU/Neural Engine, analyze performance metrics, and create high-level complexity models
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Understanding of compiler frameworks/technologies
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.
How this job compares
Set against the 6,257 open Machine Learning Engineer jobs on Olive Jobs, counted November 7, 2026.
- Pay
- This postingNot listed
- California median$180–262K/yr1,445 salary ranges
- California median$50–70/hr33 hourly ranges
- Openings
- Olive Jobs lists 1,921 open Machine Learning Engineer jobs in California and 6,257 across the US. 9% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 3 years of experience; Machine Learning Engineer postings that state a minimum ask for 5 years at the median (5,037 postings).
- Education
- This posting asks for a bachelor's degree; 2,109 of the 6,257 open Machine Learning Engineer jobs (34%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 7, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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