Senior / Staff Machine Learning Engineer

About the Role

Join the Apple Cloud AI Platform team to enable Apple's next generation of intelligent products by giving Apple's ML engineers and researchers the data systems and large-scale compute they need to build and ship models at Apple's bar for quality and privacy.

You'll work at the forefront of ML infrastructure and generative AI, where data and model workflows come together to enable intelligent experiences on Apple products and services. Build robust systems that connect scalable data pipelines with advanced ML workflows, accelerating the development of real-world AI applications.

Responsibilities

• Develop a platform for ML data and features that powers advanced GenAI applications
• Work across the full ML lifecycle, from experimentation to deployment
• Build systems spanning embeddings (generation, evaluation, ANN search, multimodal support), AI Ops, efficient inference, and a modern feature platform
• Design and maintain scalable, highly available systems that prioritize ease of use
• Shape how AI models are built, optimized, and scaled
• Work with the autonomy to experiment, the scale to make an impact, and the support to take ideas from prototype to production

Minimum Qualifications

• Strong foundation in machine learning, with hands-on experience across the end-to-end ML workflow — including data preparation, pipeline development, experimentation, evaluation, and deployment
• Expertise in building and running large scale distributed systems
• Familiarity with modern generative techniques (e.g. transformers, diffusion, retrieval-augmented generation)
• Proven experience building and delivering data and machine learning infrastructure in real-world production environments
• Familiarity with fine-tuning workflows, model optimization, and preparing models for scalable inference
• Familiarity with generative AI and its applications in accelerating and enhancing machine learning workflows
• Experience configuring, deploying and troubleshooting large scale production environments
• Experience in designing, building, and maintaining scalable, highly available systems that prioritize ease of use
• Extensive programming experience in Java, Python or Go
• Strong collaboration and communication (verbal and written) skills
• Comfortable navigating ambiguity and evolving technical landscapes, especially in fast-moving areas
• B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience

Preferred Qualifications

• Proficiency with one or more modern ML frameworks (PyTorch, JAX, or TensorFlow), particularly the data loading and dataset access layer
• Columnar and lakehouse formats: Parquet, Iceberg, Delta, or Lance
• Distributed data loading frameworks for ML: Ray Data, NVIDIA DALI, WebDataset, or Mosaic StreamingDataset
• Performance engineering for I/O-bound workloads — Arrow, zero-copy, memory mapping, async I/O
• High-throughput object storage access patterns at GPU scale
• Data lineage and governance systems (DataHub, OpenLineage, Unity Catalog, or equivalent)
• Contributions to or operational experience with Spark, Daft, Polars, or DuckDB internals
• Containerization and orchestration technologies (Docker, Kubernetes)