Machine Learning Compute Efficiency Lead, Infrastructure & Planning

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified checked Jun 13, 2026

Salary

$181K-$318K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$61,842 U.S. median for this role

Projected growth (BLS Employment Projections)

+1.9% - Slower

304% above the BLS role benchmark for operations aggregate.

Posted salary is far from this role benchmark; treat it as low confidence.

Matched to SOC 11-1021 - Operations aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Operations From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Machine Learning Compute Efficiency Lead, Infrastructure & Planning Cupertino, United States of America Apple's Platform Acceleration & Compute Efficiency (PACE) is a high-leverage team operating at the critical intersection of our ML organizations, underlying compute infrastructure, and core platform tooling. Our mission is to empower Apple's software engineering teams with efficient, scalable compute. By driving out operational friction and optimizing the broader machine learning ecosystem, we directly accelerate the pace of development across the company. As foundation models become increasingly central to Apple's user experiences, maximizing the efficiency of our ML compute is paramount. In this role, you will focus relentlessly on compute efficiency, ensuring that Apple's models run as fast, reliably, and cost-effectively as possible. You will tackle massive optimization challenges, from maximizing hardware utilization across GPUs, TPUs, and custom Apple Silicon, to shaping workload scheduling and capacity allocation for large model serving. We are seeking a Senior Architect with deep expertise in ML infrastructure to act as a linchpin for Apple's foundational inference strategy. You will be instrumental in defining, establishing, and monitoring compute efficiency metrics across the software engineering organization. By partnering closely with model developers and infrastructure providers, your work will directly reduce serving costs, shape core engineering decisions, and enable the highly efficient, scalable inference required to power Apple Intelligence for hundreds of millions of users. - Own and support ML compute management for Apple's inference workloads (GPU, TPU, and custom silicon) to enable large-scale model serving. - Collaborate closely with Apple Intelligence and ML

Read the full description at jobs.apple.com. FewerJobs shows a preview and links to the original posting.