Agent Sciences and Infrastructure Engineer, AIML

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Seattle, WA
Salary: $175,000–$308,500 / yr
Posted: 45 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $228k

This role $242k

$159k most similar roles pay here $325k

This role pays more than 57% of similar roles. Most pay $201,611–$254,750 — the shaded band above. At the midpoint, this role pays about $242k versus about $228k 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 · Agent Sciences and Infrastructure Engineer, AIML

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As an Agent Sciences and Infrastructure Engineer, AIML, you will join the Apple Intelligence Agents, Infrastructure, and Research team to build infrastructure and agentic systems used to prototype, optimize, and ship features. You will work alongside software developers and applied scientists on large language modeling, agent harnesses, evaluation, and pipelines connecting training, adaptation, and deployment. Your daily work involves designing and operating machine learning infrastructure, including training and evaluation pipelines, data and experiment tooling, serving, and agent harnesses. The role requires expertise in Python, UNIX, distributed systems, APIs, and testing while utilizing agentic coding tools. You will solve technical challenges related to on-device and server-based Apple Foundation Models by translating research into robust tooling, managing data lineage for ML pipelines at scale, and implementing post-training workflows to optimize large language models within the product ecosystem.

Skills

Python UNIX LLMs Distributed Systems APIs Agent Frameworks Tool-use Systems Benchmarking Observability Software Engineering Evaluation Infrastructure

What you'll do

Build and operate infrastructure for machine learning training, evaluation pipelines, and data tooling.
Develop agentic systems and frameworks to prototype and ship Apple Intelligence features.
Design and maintain distributed systems, APIs, and reliable code for large language models.
Create tools for LLM evaluation, tool-use systems, and data standardization at scale.
Translate complex research into robust infrastructure while identifying and resolving system bottlenecks.
Manage the end-to-end lifecycle of multi-month engineering projects from ambiguous starts to production.
Implement benchmarking and observability practices for complex machine learning systems.

What we're looking for

Ability to independently scope and lead complex, multi-month engineering projects from ambiguous starting points to production.
Experience designing, building, and operating infrastructure for machine learning training, evaluation pipelines, data tooling, or agent harnesses.
Strong software engineering fundamentals in distributed systems, APIs, testing, and maintaining reliable code.
Proficiency in Python and UNIX with a demonstrated ability to use agentic coding tools.
Experience building agent frameworks, tool-use systems, or LLM evaluation infrastructure.
Familiarity with post-training, optimizing large language models (LLMs), and associated workflows.
Ability to identify bottlenecks in research and translate them into robust tooling.
A BS with 5+ years of experience, an MS with 3+ years of experience, or a PhD with 1+ year of experience.