ML Safety Engineer

Apple Inc

Quick summary

Work type
On-site
Location
San Francisco, CA
Salary
$181,100–$272,100 / yr
Posted
50 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $196k
This role $227k
$133k most similar roles pay here $287k

This role pays more than 72% of similar roles. Most pay $154,625–$236,900 — the shaded band above. At the midpoint, this role pays about $227k versus about $196k 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.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · ML Safety Engineer

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As an ML Research Engineer at Apple Services Engineering, you will join a dedicated team focused on ensuring the safe and trustworthy development of AI features across various platforms. Your primary responsibilities include designing automated safety benchmarking methodologies, developing evaluation frameworks for assessing risks posed by media-related agents, and creating scalable tools to help engineering teams improve model performance. You will work closely with cross-functional teams to establish scientific standards and metrics for evaluating complex phenomena like multi-turn interactions, ensuring that AI experiences meet high safety and reliability benchmarks. The role requires strong proficiency in Python (pandas, NumPy, Jupyter, PyTorch), experience with large datasets and annotation tools, and a deep understanding of responsible AI practices. This position demands expertise in empirical evaluation, experimental design, and the ability to publish internal reports and external papers while staying abreast of evolving industry standards.

Skills

Python PyTorch pandas NumPy Jupyter AI/ML models LLMs program synthesis systems RAG systems reinforcement learning agentic architectures model fine-tuning CI/CD large datasets annotation tools hallucination detection model alignment taxonomies categorization schemes structured labeling frameworks

What you'll do

  • Design scientifically-grounded benchmarking methodologies for AI/ML models.
  • Develop automated evaluation pipelines to assess model outputs at scale.
  • Create datasets representing realistic and adversarial use cases across domains.
  • Define and validate new metrics for complex interaction patterns in AI systems.
  • Apply statistical rigor to ensure reproducibility in evaluation frameworks.
  • Translate experimental findings into actionable improvements for safety.

What we're looking for

  • Advanced degree (MS or PhD) in Computer Science, Software Engineering, or equivalent research/work experience.
  • 1+ years of work experience either as a postdoc or in the industry.
  • Strong background in empirical evaluation, experimental design, and benchmarking.
  • Proficiency in Python with libraries like pandas, NumPy, Jupyter, PyTorch.
  • Experience evaluating AI/ML models, preferably LLMs or program synthesis systems.
  • Ability to create datasets, tasks, and feature usage scenarios for realistic use cases.

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