Software Engineer, ML platform and Infrastructure

Apple Inc

Quick summary

Work type
On-site
Location
San Francisco, CA
Salary
$212,000–$318,400 / yr
Posted
63 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $180k
This role $265k
$124k most similar roles pay here $339k

This role pays more than 94% of similar roles. Most pay $145,000–$214,850 — the shaded band above. At the midpoint, this role pays about $265k versus about $180k 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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Software Engineer, ML platform and Infrastructure

Join Apple's Applied Machine Learning Team as a Senior Software Engineer and contribute to designing and building robust, high-performance platforms that power Data, Machine Learning, and Generative AI initiatives across the enterprise. You will architect scalable systems for large-scale distributed environments, optimizing GPU, TPU, and Inferentia utilization while integrating cutting-edge open-source technologies like LangGraph and LangChain. Your responsibilities include hands-on experience with Kubernetes, AWS/GCP, and DevOps practices to ensure system reliability and resilience. Proficiency in Python, Java, or Go is essential, along with a solid background in software engineering for complex distributed systems and expertise in operating system internals, networking protocols, and security principles. This role involves collaborating closely with cross-functional teams to influence technical strategy and roadmap decisions within the ML ecosystem at Apple scale.

What you'll do

  • Design and build robust, high-performance platforms for large-scale distributed systems.
  • Engineer systems to optimize the utilization and performance of GPUs, TPUs, and Inferentia.
  • Lead the evaluation and integration of cutting-edge open-source technologies in ML infrastructure.
  • Architect containerized workloads using Kubernetes in production environments on AWS/GCP.
  • Build highly available and resilient systems by applying deep knowledge of OS internals and networking.
  • Identify and resolve critical system bottlenecks and failures in high-stakes enterprise environments.

What we're looking for

  • 5+ years of software development experience focusing on backend systems and APIs.
  • Proficiency in Python, Java, or Go for building production-grade automation and tooling.
  • Deep hands-on experience with AWS/GCP and Kubernetes for containerized workloads.
  • Expertise in designing and engineering LLM infrastructure including GPUs, TPUs, and Inferentia.
  • Strong understanding of distributed systems, DevOps practices, and reliability engineering.
  • Ability to contribute to complex open-source ML infrastructure codebases effectively.

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