The codec deep video processing team develops machine learning algorithms to power Apple technologies with the best user visual experience. In this role, you will work closely with company-wide multiple teams and in multiple projects, from pre-training data curation to post-training data preparation, from data operator development to LLM based data assessment, from model inferencing to model re-training, in a large-scale, to help deliver new features for Apple products and bring high impact to millions of users.
Description
Join us as an ML Engineer and become the architect behind the data pipeline that power tomorrow's breakthrough Apple innovations. You will play the key role in data, the most important part that fuels the ML algorithms from conception to deployment. Working shoulder-to-shoulder with model teams, infra teams and evaluation, you'll drive the scalable data pipeline to deliver large scale of data with high quality in all aspects. Your contributions will directly shape product direction, unlock entirely new model capabilities, and define what's possible at Apple AI era.","responsibilities":"Design and develop data curation pipeline for pre-training and post-training
Work closely with model team and evaluation team to benchmark data quality
Work closely with infra team to scale up the data processing performance
Preferred Qualifications
Experience working with open-source evaluation tools like OpenEval, ELO-based ranking, or LLM-as-a-Judge frameworks.
Familiarity with prompt engineering, few-shot or zero-shot evaluation techniques.
Experience evaluating generative models (e.g., text generation, image/video generation).
Prior contributions to ML benchmarks or public evaluations.
Strong interpersonal skills.
Minimum Qualifications
Bachelor degree in Computer Science/Engineering, Mathematics or related field
A minimum of 3 years relevant industry experience
Strong experience in evaluating supervised, unsupervised, and deep learning models.
Hands-on experience working on large scale data curation pipeline for LLMs
Familiarity with multimodal models (e.g., image + text, video + audio) and related evaluation challenges.
Proficiency in Python and libraries such as NumPy, pandas, scikit-learn, PyTorch, or TensorFlow.
Strong communication skills and documentation skills, including the ability to write technical reports and present to non-technical audiences.
Apple is an equal opportunity employer that is committed to inclusion and diversity. Apple provides reasonable accommodations to applicants with disabilities and in accordance with local requirements. Apple is a drug-free workplace.