Applied AI Engineer

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$181,100–$272,100 / yr
Posted
24 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $207k
This role $227k
$154k most similar roles pay here $285k

This role pays more than 64% of similar roles. Most pay $166,902–$246,150 — the shaded band above. At the midpoint, this role pays about $227k versus about $207k 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 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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At a glance

TL;DR · Applied AI Engineer

Apple’s US Decision Intelligence team seeks a hands-on Applied AI Engineer to drive innovation in machine learning and foundational AI development. This senior-level role involves translating cutting-edge research into practical, scalable features for internal AI products, designing agentic systems that reason and act across tools and modalities, and collaborating with data science and engineering teams to embed intelligent decision-making capabilities. The ideal candidate will have a PhD or MS in Computer Science, Statistics, Mathematics, or related fields, along with extensive experience in applied AI and machine learning. Proficiency in Python (FastAPI, LangChain), RESTful API design, and hands-on experience with LLM APIs and vector databases is essential. This role requires strong technical skills, the ability to work across research and production, and effective communication with both technical and non-technical stakeholders.

What you'll do

  • Design and develop agentic AI systems that reason, plan, and act across various tools and modalities.
  • Translate research into production-ready tools by partnering with platform engineers to create SDKs and APIs.
  • Build scalable pipelines for multi-modal agent input, memory, and semantic routing in AI solutions.
  • Embed context-aware intelligence in decision-making tools through close collaboration with data science and engineering teams.
  • Lead technical decision-making on infrastructure components, embedding safety mechanisms like autonomy sliders and model monitoring.
  • Prototype and evaluate novel approaches to translate innovations from concept to production, combining research with hands-on engineering.

What we're looking for

  • PhD in a quantitative field with 3+ years of applied AI experience or MS with 6+ years of relevant experience.
  • Proficiency in Python, FastAPI, LangChain, and RESTful API design for scalable ML solutions.
  • Hands-on experience with LLM APIs, embeddings, vector databases, and agentic workflows.
  • Ability to translate research into production-ready tools by partnering with platform engineers.
  • Solid grounding in data structures, async programming, and pipeline orchestration.
  • Strong communication skills to convey technical insights to both technical and non-technical audiences.

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