Staff Senior ML Infrastructure Engineer, Foundation Model Compute Infra

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$184,700–$324,800 / yr
Posted
38 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $193k
This role $255k
$115k most similar roles pay here $347k

This role pays more than 86% of similar roles. Most pay $144,350–$241,750 — the shaded band above. At the midpoint, this role pays about $255k versus about $193k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Staff Senior ML Infrastructure Engineer, Foundation Model Compute Infra

Staff/Sr. ML Infrastructure Engineer, Foundation Model Compute Infra joins the Foundation Model Compute Infrastructure team to design and build large-scale infrastructure supporting foundation model training, fine-tuning, evaluation, and inference. The role involves developing model serving and fine-tuning services, onboarding and benchmarking new accelerators, and improving reliability, performance, scalability, and developer productivity for AI workloads. Key responsibilities include managing deployment, autoscaling, traffic management, container orchestration, and performance analysis while optimizing latency, throughput, and accelerator utilization. Candidates should possess expertise in distributed systems, cloud infrastructure, and large-scale cluster management. Required skills include Python, Go, C++, Kubernetes, and experience with GPU or TPU hardware. Familiarity with frameworks like JAX, PyTorch, TensorFlow, Ray, Pathways, or vLLM is preferred to solve complex problems involving high-performance computing for distributed machine learning workloads at production scale.

What you'll do

  • Design and evolve large-scale model serving and fine-tuning services for foundation model workloads.
  • Build infrastructure for deployment, autoscaling, traffic management, and container orchestration.
  • Optimize performance metrics including latency, throughput, availability, and accelerator utilization.
  • Implement technical optimizations such as checkpoint loading, compilation caching, and KV-cache-aware routing.
  • Onboard and benchmark new accelerator technologies into the existing compute infrastructure.
  • Integrate distributed frameworks like Pathways, Ray, and Beam into reliable and scalable services.
  • Mentor engineers and influence the technical direction of foundation model compute infrastructure.

What we're looking for

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • Master's or PhD in Computer Science or Engineering is preferred.
  • 5+ years of industry experience building large-scale distributed systems or cloud infrastructure.
  • Experience with distributed ML training or inference systems.
  • Proficiency in programming languages such as Python, Go, or C++.
  • Experience with accelerator infrastructure including GPU or TPU.
  • Experience with Kubernetes, container orchestration, or large-scale cluster management systems.
  • Familiarity with frameworks like JAX, PyTorch, TensorFlow, Ray, Pathways, or vLLM.

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