AIML Machine Learning Engineer, Evaluation, Responsible AI and Safety

Apple Inc

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Work type: On-site
Location: Cambridge, MA
Salary: $165,800–$292,400 / yr
Posted: 5 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $232k

This role $229k

$151k $308k

below market most similar roles pay here above market

This role pays less than 55% of similar roles. Most pay $208,950–$254,750 — the blue band above. At the midpoint, this role pays about $229k 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 3564 open roles on FindRole.

Listed pay typically runs $166,600–$277,600 across 2760 roles with salary data.

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TL;DR · AIML Machine Learning Engineer, Evaluation, Responsible AI and Safety

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AIML - Machine Learning Engineer, Evaluation - Responsible AI and Safety is a Senior Machine Learning Engineer role within the Responsible AI group of the Software Engineering organization. You will assess, quantify, and improve the safety and inclusivity of generative AI features, specifically focusing on large language models for text, diffusion models for images, and mixed model systems for multimodal applications. Day-to-day responsibilities include operationalizing policy into measurable criteria, designing datasets, developing LLM-judges and human-in-the-loop methods, and implementing data pipelines to inform ship/no-ship decisions. You will use Python, Pandas, and various plotting and visualization libraries to conduct failure investigations and defend safety metrics. The work involves solving complex engineering roadblocks to minimize unintended consequences across people and systems while ensuring high-quality, trusted AI experiences.

Skills

Generative AI Large Language Models Diffusion Models Multimodal Models Python Pandas Data Science Machine Learning Human-in-the-loop LLM-Judges Data Pipelines Benchmarking Agentic Systems Responsible AI

What you'll do

Operationalize policy and risk assessments into measurable criteria for generative AI products.
Design datasets and implement robust data pipelines to produce scalable safety insights.
Develop LLM-judges and human-in-the-loop methods for complex data analysis and annotation.
Analyze evaluation results and conduct failure investigations to improve feature safety.
Develop and defend safety metrics to inform ship/no-ship product decisions for stakeholders.
Monitor and align large language and multimodal models with safety and quality standards.
Conduct large-scale benchmarking across various models and capabilities.

What we're looking for

MS or PhD in a relevant science or technology field with 4+ years of experience, or a BA/BS with 8+ years of experience.
Experience with LLM-Judges and human-in-the-loop techniques, including designing annotation projects and writing guidelines for nuanced data.
Proficiency in data science, machine learning, analytics, Python, Pandas, and AI-assisted coding tools.
Experience with one or more plotting and visualization libraries.
Cross-functional collaboration skills to prioritize projects, maintain schedules, and communicate with stakeholders at all levels.
Ability to develop metrics, interpret experiments, and present findings to executives.
Comfort working with sensitive or potentially offensive content.
Experience in Responsible AI, multimodal models, or compliance with AI regulatory needs (preferred).