below marketmost similar roles pay hereabove market
This role pays less than
82%
of similar roles. Most pay
$208,556–$254,750
— the blue band above.
At the midpoint, this role pays about
$188k
versus about
$232k
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
3497 open roles
on FindRole.
Listed pay typically runs
$174,149–$277,600
across 2702 roles with salary data.
The AIML - ML Engineer, Responsible AI and Safety joins a team building large-scale machine learning systems to protect users from emerging threats and ensure product integrity. This role involves owning the full lifecycle of abuse detection models, from prototyping and data analysis to deployment, monitoring, and continuous improvement. You will design and deploy production-grade models to mitigate abuse across text, image, and audio modalities while architecting end-to-end systems for real-time automated enforcement. Key responsibilities include driving data strategies, creating synthetic data pipelines, and collaborating with researchers to translate adversarial insights into production-ready code. Required skills include proficiency in Python and deep learning toolkits like JAX, PyTorch, and Tensorflow, alongside experience with LLMs, foundation models, and diffusion models to solve complex security and safety challenges.
Design, build, and deploy production-grade ML models to detect and mitigate abuse across text, image, and audio modalities.
Own the full ML lifecycle from initial prototyping and data analysis to production deployment and continuous monitoring.
Drive data strategies by analyzing distribution gaps and building synthetic data pipelines and automated annotation systems.
Architect end-to-end systems to monitor platform activity and trigger automated enforcement actions in real-time.
Translate adversarial insights into production-ready code to build robust security and abuse detection systems.
Fine-tune and align large language models for specific security and safety applications.
Build large-scale data processing pipelines and machine learning infrastructure.
What we're looking for
2+ years experience shipping machine learning models to production.
Strong familiarity with research fundamentals, machine learning principles, and development methodologies around LLMs, foundation models, and diffusion models.
Proficient programming skills in Python and deep learning toolkits such as JAX, PyTorch, or TensorFlow.
Ability to work with sensitive and offensive content to build robust security and abuse detection systems.
BS, MS, or PhD in Computer Science, Machine Learning, or a related field (preferred).
Hands-on experience with fine-tuning or aligning large language models for security or safety applications (preferred).
Experience building large-scale data processing pipelines and ML infrastructure (preferred).
Experience driving technical projects and collaborating with large, diverse, cross-functional teams (preferred).
Machine Learning
Python
PyTorch
JAX
TensorFlow
LLMs
Foundation Models
Diffusion Models
Data Pipelines
Data Analysis
Synthetic Data
Fine-tuning
Deep Learning