AI/ML Engineer, Applied Data Science

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$172,100–$258,600 / yr
Posted
69 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $210k
This role $215k
$151k most similar roles pay here $270k

This role pays more than 56% of similar roles. Most pay $174,612–$246,150 — the shaded band above. At the midpoint, this role pays about $215k versus about $210k 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 · AI/ML Engineer, Applied Data Science

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As an AI/ML Engineer at the Applied Data Science team within Legal Operations, you will play a pivotal role in transforming innovative AI prototypes into robust production-grade systems relied upon by attorneys globally. Your responsibilities include developing prompt engineering solutions and RAG pipelines using vector databases and knowledge graphs to enhance legal workflows such as CLM and eBilling. You will also build evaluation frameworks to ensure the accuracy and safety of AI systems, collaborate with architects on system design, and support product developers with technical guidance. This role demands expertise in Python, ML frameworks like PyTorch or TensorFlow, LLM APIs, and RAG architectures, along with a solid understanding of prompt engineering techniques and experience scaling AI solutions from prototype to production.

Skills

Python PyTorch TensorFlow OpenAI Anthropic LLM APIs RAG architectures vector databases prompt engineering techniques evaluation frameworks for AI systems LangChain LlamaIndex agentic AI frameworks knowledge graphs GraphRAG patterns AI evaluation tools RAGAS DeepEval Guardrails AI NeMo Guardrails MCP integration patterns AWS

What you'll do

  • Prototype AI solutions to rapidly validate use cases and demonstrate feasibility.
  • Scale successful prototypes into production-grade systems with reliability, monitoring, and maintainability.
  • Implement prompt engineering solutions optimized for legal use cases.
  • Build and optimize RAG pipelines using vector databases and knowledge graphs.
  • Develop evaluation frameworks to measure AI accuracy, relevance, and safety across use cases.

What we're looking for

  • 4+ years experience in AI/ML engineering, NLP, or related roles
  • Proficiency in Python and ML frameworks like PyTorch, TensorFlow
  • Experience with LLM APIs from providers such as OpenAI and Anthropic
  • Expertise in RAG architectures and vector databases
  • Knowledge of prompt engineering techniques and best practices
  • Ability to take AI systems from prototype to production-grade solutions
  • Experience developing evaluation frameworks for AI system accuracy

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