Senior / Staff Machine Learning Engineer

Apple Inc.; Seattle (WA); On-site; USD 175,000 - 308,500; Full time

Job summary

Apple Inc. in Seattle, WA, is seeking engineers and researchers to join the Cloud AI Platform team, delivering data systems and compute for next‑gen ML workloads and GenAI applications across Apple products.

You’ll help scale data pipelines, embeddings, and model workflows, from experimentation to production. Ideal candidates have strong ML foundations, experience with large distributed systems, and proficiency in Python, Java or Go, plus a track record in real‑world ML infrastructure and

Qualifications

• Strong foundation in machine learning from end-to-end workflow to deployment.
• Experience building and running large-scale distributed systems.
• Familiarity with modern generative techniques (transformers, diffusion, RAG).
• Proven production experience with data and ML infrastructure.
• Experience with fine-tuning, model optimization, scalable inference.
• Exposure to GenAI applications and fast-moving tech stacks.
• Ability to deploy, troubleshoot, and scale production environments.
• Designing scalable, highly available, easy-to-use systems.

Responsibilities

• Design and build the platform behind Apple’s largest model builds — ingestion, immutable versioning, lineage, and governance across data at petabyte scale.
• Develop and evolve Python SDKs and core data libraries for ML engineers to access, transform, and load datasets.
• Build high-throughput data access and loading primitives for large GPU fleets.
• Operate distributed data pipelines across Spark, Daft, and Rust-based systems for ingestion and preparation.
• Optimize components for tight integration with PyTorch, JAX, and TensorFlow in the model dev loop.
• Onboard new data sources with researchers and product teams for GenAI workloads.
• Ensure governance, privacy controls, and end-to-end data lineage across datasets.
• Drive efficiency, reliability, and automation across data and control planes.

Skills

Large-scale distributed systems

Python

Java

Go

Machine learning fundamentals

Data pipelines

SQL

Collaboration & communication

End-to-end ML workflow

Ambiguity navigation

Education

BS, MS, or PhD in Computer Science / Engineering

Equivalent practical experience

Tools

Docker

Kubernetes

Spark

Daft

Polars

DuckDB

TensorFlow

PyTorch

JAX

Rust

Job description

Seattle, Washington, United States Software and Services

Join a team at the forefront of ML infrastructure and generative AI, where data and model workflows come together to enable the next generation of intelligent experiences on Apple products and services. We build robust systems that connect scalable data pipelines with advanced ML workflows, accelerating the development of real‑world AI applications. Our work spans the full ML lifecycle, from experimentation to deployment, and you’ll play a key role in shaping how AI models are built, optimized, and scaled. We develop a platform for ML data and features that powers advanced GenAI applications. This includes embeddings (generation, evaluation, ANN search, multimodal support), AI Ops, efficient inference, and a modern feature platform designed to streamline experimentation and drive innovation. We’re looking for engineers and researchers passionate about generative models, data‑centric ML, and intelligent systems across diverse real‑world use cases. With the autonomy to experiment, the scale to make an impact, and the support to take ideas from prototype to production, you’ll work alongside a world‑class team to build intelligent, flexible systems that make ML development faster, more reliable, and more creative.

Description

The Apple Cloud AI Platform team enables 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.

Responsibilities

• As a member of the Apple Cloud AI Platform team, your responsibilities will include:
• Design and build the platform behind Apple’s largest model builds — ingestion, immutable versioning, lineage, and governance across structured, unstructured, and multimodal data at petabyte scale, so every model run is reproducible from a versioned dataset
• Develop and evolve Python SDKs and core data libraries that ML engineers depend on to access, transform, and load model‑ready datasets across every stage of model development
• Build high‑throughput data access and loading primitives that feed Apple’s largest GPU fleets, keeping workloads compute‑bound rather than I/O‑bound
• Build and operate distributed data pipelines spanning Spark, Daft, and Rust‑based systems for ingestion, transformation, and large‑scale data preparation
• Optimize platform components for tight integration with leading ML frameworks — PyTorch, JAX, and TensorFlow — so dataset access is a first‑class concern in the model development loop
• Partner with research and product teams to onboard new data sources, and enable rapid iteration on datasets powering GenAI workloads
• Ensure governance is a first‑class platform capability: Legal Terms of Use enforcement, privacy controls, and end‑to‑end data lineage on every dataset version
• Drive efficiency, reliability, and automation across the data plane and control plane that power Apple’s ML fleet
• Continuously evolve platform capabilities to support next‑generation workloads, including foundation models, multimodal data, and retrieval‑augmented systems
• Diagnose, fix, and automate away complex issues across the stack — from ingestion pipelines to dataset APIs to ML framework integrations — to maximize uptime and throughput

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

• Experience in any of the below is preferred:
• 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)

Apple base pay is one part of our total compensation package and is determined within a range. The base pay range for this role is between $175,000 and $308,500, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace.

Learn about reasonable accommodations for job applicants.

Apple accepts applications to this posting on an ongoing basis.