GPU Engineer, Platform Architecture at Apple
Cupertino, CA 95014, USA -
Full Time


Start Date

Immediate

Expiry Date

03 Aug, 25

Salary

264200.0

Posted On

03 May, 25

Experience

3 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Performance Analysis, Software, Ml, Distributed Algorithms, Computer Science, Optimization, Compilers, Metal, Cuda

Industry

Information Technology/IT

Description

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish. Dynamic, inquisitive people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices strengthening our commitment to leave the world better than we found it! The Platform Architecture GPU group is looking for a talented GPU Engineer with strong skills in performance analysis and development, across applications and operating system components.

DESCRIPTION

As part of the team, a successful candidate will: • Analyze the performance of linear algebra and machine learning algorithms on Apple GPU platforms, pursuing investigations wherever they take you in Apple software • With our partner teams in Software Engineering and Hardware Technologies, formulate system-level strategies to address performance problems and unlock the next level of AI performance for our users • Help build the prototype software implementation, for simulated future hardware, then communicate what we learned to teams building production software for products

MINIMUM QUALIFICATIONS

  • BS degree
  • Experience with software and hardware performance analysis and optimization
  • Familiarity with GPU programming models such as Metal, CUDA, or similar

PREFERRED QUALIFICATIONS

  • MS or PhD in Computer Science, Electrical Engineering, or equivalent
  • 3+ years of relevant industry experience
  • Experience with the internals of GPU drivers, compilers and/or accelerated libraries
  • Experience working specifically in CUDA C++ on ML and/or linear algebra algorithms
  • Experience with distributed algorithms for HPC (for example, supercomputing)
  • Ability to communicate across both hardware and software organizations
Responsibilities

Please refer the Job description for details

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