ML Engineer, Proactive - Agentic Systems Evaluation

Apple Inc

Quick summary

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

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $223k
This role $174k
$111k most similar roles pay here $277k

This role pays less than 84% of similar roles. Most pay $196,562–$249,750 — the shaded band above. At the midpoint, this role pays about $174k versus about $223k 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 · ML Engineer, Proactive - Agentic Systems Evaluation

As an ML Engineer at the Proactive Intelligence team, you will play a pivotal role in designing and deploying evaluation frameworks for agentic systems, ensuring they meet high standards of quality and reliability. Your day-to-day responsibilities include creating robust metrics to measure system performance, developing MCP servers and API orchestration layers, and integrating diverse internal systems into cohesive production pipelines. You will also manage analytic dashboards to provide insights to stakeholders and collaborate with cross-functional teams. This role requires expertise in Python, along with a deep understanding of differential privacy, PII redaction, and data minimization techniques. Ideal candidates have experience with large-scale datasets, LLM-based systems, and specialized agent evaluation frameworks, as well as a background in system-level software operations to tackle the challenges of evaluating next-generation intelligent systems.

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 privacy enhancing technologies like differential privacy and PII redaction.

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 skills and experience building scalable evaluation pipelines.
  • Experience with Differential Privacy, Federated Learning, or advanced PII redaction techniques.
  • Hands-on experience with LLM-based systems and chain-of-thought reasoning.
  • Proficiency in integrating systems with external tools/APIs and analyzing execution traces.
  • Experience with compiled languages and OS-level software operations.

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