Staff ML Infra Platform Architect

Apple Inc.; Cupertino, Northern (CA, KY); Hybrid; USD 185,000 - 325,000; Full time

Job summary

Apple Inc. in Cupertino, CA, is seeking a Staff ML Infrastructure Engineer to own the data and feature platform that powers large-scale model training and inference across Apple products.

You will drive architecture for ingestion, versioning, lineage, and governance at petabyte scale, and enable efficient data delivery to GPU/TPU fleets while mentoring engineers and shaping the SDKs and interfaces used across teams.

Qualifications

• 10+ years in machine learning infrastructure or distributed data systems.
• Proven experience delivering large-scale ML infrastructure in production.
• Ability to set technical direction and drive delivery across teams.
• Strong Python and systems language skills; Rust preferred; performance tuning for I/O.
• Familiar with columnar/lakehouse formats and end-to-end ML workflows.

Responsibilities

• Own platform architecture for ingestion, versioning, lineage, and governance at petabyte scale.
• Define data delivery to large GPU/TPU fleets to keep training compute bound.
• Shape SDKs, libraries, and data abstractions across teams (data, embeddings, research).
• Mentor engineers, lead design reviews, and escalate complex issues.
• Collaborate with research and product leadership on platform roadmap.

Skills

Python

Rust

C++

Go

Performance tuning

Distributed systems

Data pipelines

ML infrastructure

Arrow

I/O optimization

Education

BS/MS/PhD in Computer Science or related

Tools

Docker

Kubernetes

Spark

Daft

Polars

DuckDB

DataHub

OpenLineage

Iceberg

Job description

Apple Inc. in Cupertino, CA, is seeking a Staff ML Infrastructure Engineer to own the data and feature platform that powers large-scale model training and inference across Apple products.

You will drive architecture for ingestion, versioning, lineage, and governance at petabyte scale, and enable efficient data delivery to GPU/TPU fleets while mentoring engineers and shaping the SDKs and interfaces used across teams.