Senior ML Engineer, Responsible AI and Safety

Apple Inc

Confirmed live 2 days ago Trusted

Quick summary

Work type: On-site
Location: Seattle, WA
Salary: $175,000–$308,500 / yr
Posted: 41 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $232k

This role $242k

$159k most similar roles pay here $325k

This role pays more than 53% of similar roles. Most pay $208,906–$254,750 — the shaded band above. At the midpoint, this role pays about $242k versus about $232k for comparable roles.

Based on 240 similar postings.

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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 · Senior ML Engineer, Responsible AI and Safety

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AIML - Senior ML Engineer, Responsible AI and Safety joins the Human-Centered Machine Intelligence organization to manage the end-to-end responsible AI lifecycle for generative features. This role involves assessing risks, defining safety policies, developing mitigation strategies, and driving continuous improvements for large language and multimodal models. You will build tools, datasets, and evaluation methods to monitor, diagnose failures, and improve model safety through human and automated feedback. The position requires expertise in Python, Pandas, and data science libraries to perform analysis and visualization. Key technical requirements include experience with Transformers, LLMs, VLMs, NLP, or Computer Vision. You will address critical challenges in fairness, robustness, uncertainty, and interpretability while managing complex, multi-labeled data. This role focuses on the intersection of policy and product to ensure safety alignment for generative models across various deployment stages.

Skills

Generative AI LLMs VLMs Transformers NLP Computer Vision Python Pandas Data Analysis Model Explainability Robustness Testing Failure Analysis Multimodal Datasets Machine Learning

What you'll do

Manage the end-to-end responsible AI lifecycle including risk assessment, policy definition, and mitigation strategies.
Develop safety alignment strategies and architectural mitigations for large language and multimodal models.
Create tools, datasets, and evaluation methods to monitor and diagnose model failures.
Implement human and automated feedback loops to improve feature safety post-launch.
Conduct research on fairness, robustness, uncertainty, and the societal impacts of generative AI.
Analyze complex, multi-labeled data to design and support robust evaluation systems.
Perform failure analysis and quality engineering for machine learning-driven systems at scale.

What we're looking for

At least 3 years of experience in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision.
Proficiency in Python and data science libraries like Pandas for data analysis and applied ML workflows.
Experience designing and supporting human and automated evaluations for complex, nuanced, or multi-labeled data.
Hands-on experience collecting and analyzing language, vision, or multimodal datasets.
Background in failure analysis, quality engineering, or robustness testing for ML-driven systems.
Ability to translate technical insights for cross-functional partners, senior leadership, and executives.
Comfort working with sensitive or potentially offensive content.
A BS, MS, or PhD in Computer Science, Machine Learning, or a related field is preferred.

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