Senior Research Engineer, Training Data Infrastructure in Foundation Models

Apple • Cupertino, CA

3h

About The Position

Our team is dedicated to solving the high-quality training data problem at the
scale required to train advanced Foundation Models. We believe that the advanced
model performance (including reasoning, coding, and agentic planning)
fundamentally depends on a data-centric approach to Machine Learning. Our
objective is to engineer a large-scale system that acquires, processes, and
curates the data required to advance the state of the art in Artificial
Intelligence. We are seeking a Senior Research Engineer who possesses a deep
understanding of distributed systems and a strong intuition for Machine
Learning. You will join a culture that values engineering craftsmanship,
privacy, and rigorous scientific inquiry, utilizing advanced cloud technologies
to build the data systems that powers our most capable models.

This position operates at the convergence of Software Engineering and Machine
Learning Research. Unlike traditional backend roles, this position requires you
to design systems where the outcome is the statistical distribution and quality
of data itself. You will work alongside Research Scientists to transform
theoretical observations into concrete, scalable engineering solutions. Your
core focus will be the architecture of our Data Acquisition, Processing, and
Repository Management systems for Large Model training. You will lead technical
efforts to enable active, quality-driven data curation, including filtering,
deduping, synthetic data generation and data mixing, ensuring our models are
trained on the highest-quality information available.

Requirements

• Bachelor’s degree in Computer Science, Electrical Engineering, or Mathematics.
• 4+ years of software engineering experience with a specific focus on Data Infrastructure, Distributed Systems, or AI/ML Engineering.
• Expert fluency in Python, and strong competence in system languages such as C++.
• Extensive experience architecting solutions on major public cloud platforms (e.g. GCP) to build scalable data systems (e.g. with Apache Beam, GCS)
• Deep experience profiling and optimizing high-throughput data systems. Demonstrated ability to debug distributed bottlenecks (e.g., stragglers, I/O saturation), optimize data formats and provide efficient data storage solutions.

Nice To Haves

• Experience working within or closely with ML research organizations (e.g., as a Research Engineer), with an ability to translate research results into engineering implementations.
• Familiarity with lifecycle of modern LLM training, end-to-end workflows, and underlying system architecture.
• Experience in processing complex data modalities beyond plain text, such as source code repositories, images, videos, and audios.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees