Staff ML Infrastructure Engineer at Apple

Department: Software and Services

Compensation · Listed in posting

$184,700 – $324,800

Location: Cupertino, California
Type: Full-time, Other
Level: staff+
Posted: Sep 24, 2026

Description

Apple is hiring a Staff ML Infrastructure Engineer to set technical direction for the data and ML platform powering its largest model builds. The role owns architecture for petabyte-scale ingestion, versioning, lineage, governance, and high-throughput delivery to GPU and TPU fleets, defines data-access and loading strategies, shapes SDK and core-library interfaces, and drives reliability, automation, and cross-team alignment. The engineer will also mentor senior engineers, lead design reviews, and partner with research and product leadership on next-generation ML workloads.

Required Skills

Python
Rust
C++
Go
Arrow
Parquet
Iceberg
Delta
Lance
Kubernetes

Additional Information

Minimum Education: Bachelor's, master's, or Ph.D. in Computer Science or Computer Engineering, or equivalent practical experience
Required Previous Experiences: 10+ years of experience in machine learning infrastructure, distributed data systems, or a related field
10+ years of experience building and shipping large-scale data or ML infrastructure and platforms in production
Extensive experience architecting and delivering large-scale distributed data or ML infrastructure used by multiple teams or products in production
Experience setting technical direction and driving delivery across teams
Experience with Python, a systems language, and performance engineering for I/O-bound workloads
Experience with columnar and lakehouse formats at scale
Experience with end-to-end ML workflows and data systems for training and inference
Experience with modern ML and generative techniques
Experience designing highly available systems and mentoring engineers
Experience collaborating and aligning multiple teams around technical direction
Preferred Qualifications: Experience defining data or ML platform architecture adopted across an organization
Experience with data-loading and dataset-access layers of PyTorch, JAX, or TensorFlow
Experience with distributed ML data-loading frameworks
Experience feeding data to GPU or TPU fleets at scale
Experience with data lineage and governance systems
Experience with Spark, Daft, Polars, or DuckDB internals
Experience with Docker and Kubernetes
Translation Company Name: Apple

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