Machine Learning Engineer, Platform Architecture

Apple Inc.
Cupertino, United States of America
1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 272K

Job location

Cupertino, United States of America

Tech stack

C++
Python
Machine Learning
Systems Architecture
PyTorch

Job 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.","responsibilities":"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.

Requirements

Do you have experience in System architecture design?, Do you have a Bachelor's degree?, 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

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

Benefits & conditions

4.14.1 out of 5 stars Cupertino, CA $147,400 - $272,100 a year, Pulled from the full job description

  • Employee stock purchase plan
  • Health insurance
  • Retirement plan
  • Dental insurance
  • RSU, 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 $147,400 and $272,100, 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.

About the company

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.

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