The System Intelligence and Machine Learning team is in charge of creating datasets that power many of Apple’s intelligent software. Our datasets range from very small targeted sets to Petabyte scale datasets. We are looking for an expert Machine Learning engineer, or Data Scientist who can help create and improve the datasets used in Generative AI through proven understanding and usage of ML and stats.

As a senior member of the System Intelligence and Machine Learning Data team, you will be using Apple technologies to refine our datasets, perform ML-based QA, remove toxicity and select the right images, videos or texts through active selection and model-in-the-loop methodologies. Focus areas range from text processing across many languages (toxic language detection and removal, identification of colloquial vs formal language) to image and video understanding, deduplication and processing. As part of this role you will also own our data synthesis efforts in various modalities including image, text, videos and audio.

In this role, you will be working to deepen our understanding of how various datasets can improve the quality of Apple’s ML models on a range of products. You will particularly help shape Apple’s Datasets that are used for generative AI by removing irrelevant or toxic assets, selecting the right assets by employing various asset selection algorithms, and synthesizing new datasets by utilizing Apple proprietary ML models. For this, you will also use your stats and ML background to build models and algorithms that can select the right assets for ML experiences from a large pool of available assets, and you will work with our data engineers to put your models in data pipelines to run on large scale datasets.

In our team, you are encouraged to collaborate with other AIML product stakeholders and partners to understand needs, design Machine Learning models that help us better understand our data and automatically pick the right assets for ML training. Our Data Scientists actively evaluate and present the progress of their work. Your creative decision making will be applied daily.

Bachelors, Masters or PhD degree in Computer Science, Statistics, Mathematics, Engineering; or equivalent experience.Proven track record in a Machine Learning Engineering or Applied Scientist role, preferably in a technology company.Familiarity with a broad range of Machine Learning techniques and relevant statistical packages to engineer ML solutions end-to-end.