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Senior Research Engineer, Training Data Infrastructure in Foundation Models

Apple· Software and Services
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Cupertino, California$184.7k - $324.8kFull-timePosted 6mo ago

About the role

Senior role focused on architecture and engineering of data acquisition, processing, and repository management for large model training. Combines software engineering with ML research to deliver high-quality, scalable data systems for Apple’s foundation models, with emphasis on privacy, efficiency, and hardware optimization for Apple silicon.

Responsibilities

  • Architect Scalable Ingestion Systems: Design and implement high-throughput distributed systems to ingest petabytes of text and multimodal data from diverse sources, including web crawls and third-party partnerships.
  • Repository Optimization: Manage the lifecycle of large-scale datasets across data storage and high-performance file systems. Optimize data formats for efficient random access and sequential scanning during model training.
  • Data Governance & Privacy: Engineer robust data governance and privacy solutions for the training data, in collaboration with compliance and legal teams, to ensure adherence to stringent regulatory standards.
  • High-Performance Processing Pipelines: Build and maintain distributed data processing workflows using advanced frameworks on cloud infrastructure (e.g., GCP, AWS).
  • Algorithmic Data Curation: Implement sophisticated data filtering and selection logic to remove low-quality content. Develop semantic deduplication at scale to prevent model memorization and improve training efficiency.
  • Decontamination Removal: Design automated systems to detect and remove benchmark leakage, ensuring that evaluation datasets remain strictly isolated from training corpora.
  • Infrastructure for Scaling Laws: Collaborate with researchers to enable data ablations and scaling experiments. Build tools to support systematic data mixture optimization and empirically data studies.

Qualifications

  • Education: Bachelor’s degree in Computer Science, Electrical Engineering, or Mathematics.
  • Technical Expertise: 4+ years of software engineering experience with a specific focus on Data Infrastructure, Distributed Systems, or AI/ML Engineering.
  • Language Proficiency: Expert fluency in Python, and strong competence in system languages such as C++.
  • Cloud Architecture: Extensive experience architecting solutions on major public cloud platforms (e.g. GCP) to build scalable data systems (e.g. with Apache Beam, GCS)
  • Performance Engineering: 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.
  • Research Collaboration: 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.
  • Domain Knowledge: Familiarity with lifecycle of modern LLM training, end-to-end workflows, and underlying system architecture.
  • Complex Data Types: Experience in processing complex data modalities beyond plain text, such as source code repositories, images, videos, and audios.

Skills

Required:PythonC++Distributed SystemsData Governance & Privacy

Benefits

  • Comprehensive medical and dental coverage
  • Retirement benefits
  • Discounted products and free services
  • Educational reimbursement for advancing your career
  • Discretionary bonuses or commission payments (where eligible)
  • Relocation assistance (where eligible)
  • Stock purchase opportunities via Employee Stock Purchase Plan
Last updated Jul 3, 2026. Interested? Apply on the company site.

About Apple

Discover the innovative world of Apple and shop everything iPhone, iPad, Apple Watch, Mac, and Apple TV, plus explore accessories, entertainment, and expert device support.

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