Senior Machine Learning Engineer

Build the ML data foundation for large-scale training and generative AI. Apple’s AI Platform team is hiring a Senior Machine Learning Engineer in Cupertino, CA (onsite). In this role, you will own the data layer that powers how models learn and how training fleets access data, with a focus on ingestion, versioning, lineage, governance, and high-throughput loading. You will also help develop the platform capabilities that support advanced GenAI applications, from embeddings and ANN search to AI Ops and efficient inference.

What you’ll do

• Own and ship major components of the AI Platform team’s platform for ML data and features.
• Deliver the data layer large-scale model training depends on, including ingestion, versioning, lineage, and governance, plus high-throughput data loading into the training fleet.
• Develop ML data and feature platform capabilities used by advanced GenAI applications, including embeddings (generation, evaluation, ANN search, and multimodal support), AI Ops, efficient inference, and tools that streamline experimentation.
• Help shape how AI models are built, optimized, and scaled across the full ML lifecycle from experimentation through deployment.

Key requirements

• 5+ years of work experience in machine learning infrastructure, distributed data systems, or a related field.
• 5+ years building and shipping data or ML infrastructure and systems in production.
• Experience operating production systems, including monitoring, observability, on-call, and incident response.
• Strong programming skills in Python, plus a systems language for performance-critical work (Rust strongly preferred; C++ or Go acceptable).
• Familiarity with columnar and lakehouse formats (Parquet, Iceberg, Delta, or Lance) and the trade-offs between them.
• Hands-on performance engineering for I/O-bound workloads, including Arrow, zero-copy, memory mapping, async I/O, and high-throughput object storage access patterns.
• Working knowledge of the end-to-end ML workflow and how training and inference consume data, enough to design data systems that fit those workloads.
• Knowledge of modern ML and generative techniques (transformers, diffusion, retrieval-augmented generation, fine-tuning) at a level needed to design for data consumers.
• Experience designing and operating scalable, highly available systems that emphasize ease of use for engineers.
• Strong collaboration skills and written and verbal communication skills.
• B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience.

Technologies you may work with

Python, Rust, C++, Go, Parquet, Iceberg, Delta, Lance, Arrow, transformers, diffusion, retrieval-augmented generation, fine-tuning, PyTorch, JAX, TensorFlow, Ray Data, NVIDIA DALI, WebDataset, Mosaic StreamingDataset, DataHub, OpenLineage, Unity Catalog, Spark, Daft, Polars, DuckDB, Docker, Kubernetes.

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Discretionary employee stock programs, including eligibility for the Employee Stock Purchase Plan at a discount
• Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
• This role might be eligible for discretionary bonuses or commission payments and relocation

Compensation

Base pay range: USD 184,700 - 324,800 per year. Base pay depends on skills, qualifications, experience, and location. Base pay is one part of the total compensation package.