This listing does not state pay. Across 48 open machine learning engineer listings that state pay, the middle half runs $167,500 to $239,500 and the median is $199,000.

Listed pay is what employers advertise, not what people are paid.

Machine Learning Engineer salaries by state · Check your own pay

How AI is used in this kind of work

Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

Check how this applies to your own job

Apple has filed 4 layoff notices in the last twelve months, covering 225 workers, most recently August 2026. These are public filings with state labor departments, and an open role can sit alongside them. See the filings

Skills this job asks for

Say which you have and which you want to build. We use it to match you to jobs like this one.

Machine learning

About the job

Would you like to contribute to Machine Learning and Generative AI technologies? Are you passionate about the integrity of the data that powers AI systems at scale? Do you believe that trustworthy data is the foundation of every great model? We truly believe it is!

We are defining what exceptional data quality looks like for machine learning across Wallet, Payments, and Commerce. As a Machine Learning Engineer, AI/ML Model Quality, you will build and maintain intelligent systems, validation frameworks, synthetic data generation models and monitoring pipelines that keep our data ecosystem healthy — ensuring that every model we build is trained, evaluated, and deployed on data we can trust. Your work sits at the foundation of every ML feature that reaches hundreds of millions of users.

You'll work at the intersection of machine learning, statistical rigor and production systems, collaborating closely with Data Engineering, Privacy, and Legal teams. This unique opportunity puts you at the center of ML and AI quality — owning the health of training and validation datasets, defining and analyzing observability metrics, building models to calibrate & measure robustness, and leading telemetry analysis across GenAI workflows — ensuring Apple's financial features are built on the highest-quality data, whether powering conventional ML models or the latest generative AI systems.