Machine Learning Engineering Manager, Responsible AI and Safety

Apple Inc

Confirmed live yesterday Trusted

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$206,200–$356,400 / yr
Posted
48 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $227k
This role $281k
$164k most similar roles pay here $377k

This role pays more than 85% of similar roles. Most pay $199,350–$254,812 — the shaded band above. At the midpoint, this role pays about $281k versus about $227k 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 · Machine Learning Engineering Manager, Responsible AI and Safety

Machine Learning Engineering Manager, Responsible AI and Safety - AIML/SWE leads a team within the Human-Centered Machine Intelligence organization focused on the responsible AI lifecycle for generative features. You will manage machine learning engineers to assess risks, define policies, and develop mitigation strategies for large language and multimodal models. The role involves providing technical direction for dataset design and safety alignment while overseeing the implementation of mitigation architectures in production. Day-to-day tasks include analyzing evaluation results, conducting failure investigations, and utilizing human and automated feedback to improve feature safety. Required skills include proficiency in Python and data science libraries like Pandas, along with experience in NLP, Computer Vision, and Transformers. You will address technical challenges regarding model interpretability, fairness, and bias while ensuring the safety of global generative AI products through cross-functional collaboration.

What you'll do

  • Lead a team of machine learning engineers to manage the end-to-end responsible AI lifecycle.
  • Define safety policies and mitigation strategies for large language and multimodal models.
  • Provide technical direction for dataset design and safety alignment strategies.
  • Oversee the implementation of mitigation architectures in production environments.
  • Analyze evaluation results and conduct failure investigations to improve feature safety.
  • Translate complex technical insights into actionable recommendations for cross-functional partners and executives.
  • Mentor and develop a high-performing team while fostering a culture of technical excellence.

What we're looking for

  • 5+ years of experience in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision.
  • 2+ years of experience directly managing engineering teams.
  • Proficiency in Python and data science libraries like Pandas for analysis and ML workflows.
  • Experience collecting and analyzing language, vision, or multimodal datasets.
  • Background in failure analysis, quality engineering, or robustness testing for ML-driven systems.
  • Ability to interpret outputs from human and automated evaluations of complex or multi-labeled data.
  • Proven ability to translate complex technical insights for cross-functional partners and senior leadership.
  • BS, MS, or PhD in Computer Science, Machine Learning, or a related field, or equivalent experience.

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