ML Engineer, Proactive - Agentic Systems Evaluation

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$126,800–$220,900 / yr
Posted
43 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $219k
This role $174k
$111k most similar roles pay here $275k

This role pays less than 81% of similar roles. Most pay $189,093–$249,750 — the shaded band above. At the midpoint, this role pays about $174k versus about $219k 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 · ML Engineer, Proactive - Agentic Systems Evaluation

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As an ML Engineer at the Proactive Intelligence team, you will play a crucial role in architecting and deploying evaluation frameworks for agentic systems, focusing on measuring quality, reasoning, and tool-use accuracy. Your day-to-day responsibilities include designing MCP servers and API orchestration layers to ensure reliable tool use, integrating diverse internal systems into cohesive production pipelines, and creating analytic dashboards for stakeholders. You will work with sensitive data, requiring expertise in privacy-enhancing technologies like differential privacy and PII redaction. The ideal candidate has a strong background in machine learning engineering, software fundamentals, and experience with Python, as well as familiarity with advanced techniques such as federated learning and chain-of-thought reasoning. This role is pivotal in advancing scalable automated processes for evaluating the next generation of personalized intelligence systems.

Skills

Python Differential Privacy Federated Learning PII Redaction LLMs Chain-of-Thought Reasoning Prompt Engineering API Integration Agent Evaluation Frameworks Prometheus Grafana CI/CD MCP Servers Data Minimization

What you'll do

  • Design and implement evaluation frameworks to measure quality, reasoning, and tool-use accuracy of agentic systems.
  • Develop MCP servers and API orchestration layers for reliable tool use in agentic systems.
  • Integrate internal systems into cohesive production-ready ML pipelines.
  • Create analytic dashboards to surface evaluation insights to stakeholders.
  • Apply differential privacy and PII redaction techniques to handle sensitive data.

What we're looking for

  • MS or PhD in Computer Science, Machine Learning, Statistics, or equivalent practical experience.
  • 3+ years of industry experience in ML Engineering or Applied Science.
  • Strong Python programming skills and experience with scalable data pipelines.
  • Experience applying Differential Privacy, Federated Learning, or advanced PII redaction techniques.
  • Hands-on experience building or testing LLM-based systems with chain-of-thought reasoning.
  • Proficiency in evaluating systems that integrate with external tools/APIs and analyzing execution traces.

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