About this opportunity
Apple Inc. lists this AIML - Applied ML Engineer, Responsible AI and Safety opportunity in cupertino, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
AIML - ML Engineer, Responsible AI and Safety
Cupertino, California, United States Machine Learning and AI
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.
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.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant
At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here - in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
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Apple accepts applications to this posting on an ongoing basis.
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Worksite address
cupertino, CA, 95014, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.