JobsGPU ML Engineer
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GPU ML Engineer

Apple

Location

Cupertino, CA

Type

Full-time

Posted

7/24/2026

Compensation

Not listed

Undergraduate with 2+ Years of Experience
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·FY 2025

Job description

Apple's Compute Frameworks team is focused on developing high-performance data parallel algorithms for various platforms including iOS, macOS, and Apple TV. The team is seeking skilled machine learning and GPU programming engineers to enhance compute solutions for Apple Silicon. This role offers the chance to influence the design of future GPU architectures. Candidates should be dedicated and passionate about their work.

Requirements

  • Technical BS/MS degree or equivalent experience
  • At least 2 years of experience in GPU compute kernel framework development
  • Experience with system level programming and computer architecture
  • Experience in high performance parallel programming and GPU programming
  • Excellent programming and problem-solving skills
  • Strong communication and collaboration skills
  • Good understanding of machine learning fundamentals
  • Background in mathematics, including linear algebra and numerical methods is a plus

Responsibilities

  • Develop and optimize GPU compute kernel frameworks
  • Collaborate with team members to enhance compute solutions
  • Influence the design of compute and programming models for next generation GPU architectures
  • Apply machine learning techniques to accelerate networks on Apple Silicon

Benefits

  • Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.

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