Senior Machine Learning Engineer
Core
Build and own high-throughput data access and loading primitives for Apple's largest GPU and TPU fleets to keep training compute-bound rather than I/O-bound.
Role type
Senior ML Infrastructure Engineer
Builds
Data pipelines, data libraries, SDKs, and platform components for model training at scale
Domain
Generative AI, ML Infrastructure, Distributed Data Systems
Deliverable
infrastructure
Required skills
Python, Rust, distributed data systems, high-throughput I/O engineering, data lineage and governance, PyTorch/JAX/TensorFlow integration, observability, incident response
Preferred skills
Ray Data, NVIDIA DALI, WebDataset, Mosaic StreamingDataset, Spark/Daft/Polars internals, Kubernetes, containerization
Technologies
Python, Rust, Spark, Daft, PyTorch, JAX, TensorFlow, Parquet, Iceberg, Delta, Lance, Arrow, Docker, Kubernetes
Responsibilities
Build high-throughput data loading primitives; Develop Python and Rust data libraries and SDKs; Operate distributed data pipelines for ingestion and transformation; Contribute to platform components for ingestion, versioning, lineage, and governance; Integrate data-loading layers with PyTorch, JAX, and TensorFlow; Partner with teams to onboard data sources; Diagnose and automate issues across the stack
Seniority
Senior, hands-on IC
