AIML - Applied ML Engineer, Responsible AI and Safety

Join a team at the forefront of defending Apple's ecosystem. We build the

large-scale machine learning systems that protect millions of users from

emerging threats and ensure the integrity of our products. We are looking for an

experienced Applied ML Engineer who has a proven track record of shipping

production models. The ideal candidate is passionate about tackling complex

safety and security challenges using state-of-the-art techniques. In this role,

you will design, build, and deploy the critical machine learning systems that

are foundational to the safety of Apple's products, all while upholding our deep

commitment to user privacy.

DESCRIPTION

As engineer on this team, you will own the full lifecycle of our abuse detection

machine learning models. You will collaborate closely with researchers to

understand the threat landscape and partner with software and product teams to

deploy robust, scalable defenses. We believe the most effective security systems

are built by engineers who can translate adversarial insights into

production-ready code. Your work will directly contribute to the architecture of

Apple's AI platform and protect users from real-world harm. Here is what you

will do: * Design, build, and deploy production-grade ML models to detect and

mitigate abuse across multiple modalities (text, image, audio). * Own the full

ML lifecycle: from prototyping and data analysis to deployment, monitoring, and

the continuous improvement of models in production. * Drive the data strategy to

continuously improve model performance by analyzing distribution gaps,

contributing to synthetic data pipelines, and creating automated annotation

systems. * Architect end-to-end systems for monitoring platform activity,

detecting misuse, and triggering automated enforcement actions in real-time. *

Collaborate with cross-functional partners in engineering, research, and product

to define project requirements, establish technical direction, and deliver

robust security solutions.

MINIMUM QUALIFICATIONS

2+ years experience shipping machine learning models to production. You have

owned the end-to-end lifecycle of a model, from development to deployment and

maintenance. 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 (e.g. JAX, PyTorch, Tensorflow) Ability to work with sensitive and

offensive content as part of building robust security and abuse detection

systems.

PREFERRED QUALIFICATIONS

BS, MS or PhD in Computer Science, Machine Learning, or related fields or an

equivalent qualification acquired through other avenues Hands-on experience with

fine-tuning or aligning large language models for security or safety

applications. Experience building large-scale data processing pipelines and ML

infrastructure. Experience driving technical projects and collaborating with

large, diverse, cross-functional teams.