Data Scientist - Intelligent Experiences, MLO

Apple • Cupertino, CA

6d

About The Position

The ML Data team within Apple’s Intelligent System Experience group builds high-quality, large-scale datasets used to train machine-learning features across Apple products, including iPhone, iPad, Mac, Apple Watch, and AirPods. This role focuses on shaping training data for upcoming multimodal features and contributes to shipping products from the first week, working with petabytes of multimodal data.

The Data Scientist will design and operate the end-to-end data lifecycle supporting the training, fine-tuning, and evaluation of large language models and diffusion models. The work includes building distributed pipelines to clean, deduplicate, and enrich large multimodal datasets; creating synthetic-data pipelines using LLM-based generators, validators, and judges; and engineering multi-step, tool-using LLM workflows that scale human judgment across large datasets.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related engineering field.
• At least 5 years of hands-on experience applying NLP, computer vision, or multimodal machine learning to production systems, including experience with large-scale data pipelines.

Nice To Haves

• Experience prompting, fine-tuning, and evaluating LLMs or vision-language/diffusion models for downstream tasks.
• Experience with parameter-efficient fine-tuning (LoRA/QLoRA), preference optimization (RLHF, DPO), RAG, and retrieval-based data curation.
• Experience designing, evaluating, and productionizing data-science algorithms for data curation, filtering, deduplication, and down-selection.
• Experience designing controlled experiments or ablation studies to understand the effect of data on model quality.
• Experience building agentic or multi-agent tool-using LLM systems and human-in-the-loop workflows, calibrating judges against human labels, and mitigating failure modes.
• Strong software engineering skills, including 5+ years of experience with Python, workflow orchestration such as Airflow, cloud platforms such as AWS or GCP, and distributed data-processing frameworks such as Spark or Ray at large scale.
• Publication record or open-source contributions in NLP, computer vision, or generative AI.
• Familiarity with privacy-preserving data techniques, such as differential privacy or on-device data constraints.

Responsibilities

• Design and operate the end-to-end data lifecycle for training, fine-tuning, and evaluating large language models and diffusion models.
• Build distributed pipelines to clean, deduplicate, and enrich large multimodal datasets.
• Build synthetic-data generation pipelines using LLM-based generators, validators, and judges.
• Engineer agentic, multi-step, tool-using LLM workflows to scale human judgment across data.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior