Apple

Machine Learning Engineer, Platform Architecture - Full-time

Cupertino, California, USFull-time5 days agovia Snagajob

Salary

-

Job type

Full-time

Location

Cupertino, California, US

Remote

No

Posted

5 days ago

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Job description

**Role Number:** 200624634-0836

  • *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!

  • *Description**

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.

  • *Minimum Qualifications**

+ Bachelor’s degree

+ Ability to program in C/C++ and/or Python

+ Knowledge of computer architecture fundamentals

+ Domain knowledge in at least one hardware IP: ML HW accelerators or processing units such as GPU, image/video, CPUs, or similar

  • *Preferred Qualifications**

+ MS or PhD in EE/CE/CS or related field, or 3+ years of relevant experience

+ Experience with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms

+ Experience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environments

+ Experience in creating SoC or IP performance models/simulations

+ Verbal and written communication skills for collaborating with partner teams

+ Ability to prototype algorithms on CPU/GPU/Neural Engine, analyze performance metrics, and create high-level complexity models

+ 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. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf) .

  • *Role Number:** 200624634-0836
  • *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!

  • *Description**

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.

  • *Minimum Qualifications**

+ Bachelor’s degree

+ Ability to program in C/C++ and/or Python

+ Knowledge of computer architecture fundamentals

+ Domain knowledge in at least one hardware IP: ML HW accelerators or processing units such as GPU, image/video, CPUs, or similar

  • *Preferred Qualifications**

+ MS or PhD in EE/CE/CS or related field, or 3+ years of relevant experience

+ Experience with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms

+ Experience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environments

+ Experience in creating SoC or IP performance models/simulations

+ Verbal and written communication skills for collaborating with partner teams

+ Ability to prototype algorithms on CPU/GPU/Neural Engine, analyze performance metrics, and create high-level complexity models

+ 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. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf) .

Responsibilities

  • 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
  • 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

Qualifications

  • Bachelor’s degree
  • Ability to program in C/C++ and/or Python
  • Knowledge of computer architecture fundamentals
  • Domain knowledge in at least one hardware IP: ML HW accelerators or processing units such as GPU, image/video, CPUs, or similar
  • MS or PhD in EE/CE/CS or related field, or 3+ years of relevant experience
  • Experience with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms
  • Experience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environments
  • Experience in creating SoC or IP performance models/simulations
  • Verbal and written communication skills for collaborating with partner teams
  • Ability to prototype algorithms on CPU/GPU/Neural Engine, analyze performance metrics, and create high-level complexity models
  • Understanding of compiler frameworks/technologies
  • Bachelor’s degree
  • Ability to program in C/C++ and/or Python
  • Knowledge of computer architecture fundamentals
  • Domain knowledge in at least one hardware IP: ML HW accelerators or processing units such as GPU, image/video, CPUs, or similar
  • MS or PhD in EE/CE/CS or related field, or 3+ years of relevant experience
  • Experience with ML frameworks (e.g. PyTorch) and efficient implementations of machine learning algorithms
  • Experience in optimizing and deploying ML models and/or runtime frameworks in production inference/training environments
  • Experience in creating SoC or IP performance models/simulations
  • Verbal and written communication skills for collaborating with partner teams
  • Ability to prototype algorithms on CPU/GPU/Neural Engine, analyze performance metrics, and create high-level complexity models
  • Understanding of compiler frameworks/technologies

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