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# Machine Learning Engineer, Data for Foundation Models

- **Company:** Apple Inc.
- **Location:** Cupertino, CA, United States
- **Experience:** Experienced
- **Salary:** $150,400.0
- **Contract:** Permanent contract
- **Skills:** Training Data, Artificial Intelligence, Big Data, Apache Hadoop, Machine Learning, Tensorflow, Pytorch, Large Language Models, Generative AI, Information Technology, Stable Diffusion, Data Generation
- **Published:** October 15, 2026
- **Apply:** https://www.jobmonkeyjobs.com/career/28110059/Machine-Learning-Engineer-Data-For-Foundation-Models-California-Cupertino-7413

## About the Role

M.S. or PhD in Computer Science or a related field such as Electrical Engineering, Robotics, Statistics, Applied Mathematics, or equivalent experience

3+ years of experience improving modern image generation or image understanding models through data ablation experiments

Knowledge of ML frameworks such as PyTorch / JAX. Experience leveraging large-scale data frameworks such as Hadoop / Ray.

Experience working in an academic or industrial research environment

Excellent communication skills, bias-for-action and ability to drive clarity in ambiguous circumstances

Preferred Qualifications

Hands-on experience improving the quality of diffusion image generation models through training data improvements

Track record of strong industrial research output, shipped complex projects or published at top-tier venues

## Description

We are seeking a machine learning research engineer with experience building high-quality datasets for foundation model training. The ideal candidate has solid ML fundamentals, experience with applied research, and hands-on knowledge of constructing large scale and targeted datasets involving image or video to improve the quality of diffusion or auto-regressive foundation models. You will stay at the forefront of the latest AI research to rapidly adopt impactful developments while simultaneously pioneering proprietary and experimental ideas. You will design data annotation, enrichment, curation and synthetic data generation pipelines using classic or genAI tools to improve model quality along specific dimensions aligned with Apple's unique product offerings.