Apple · Seattle

Staff Machine Learning Engineer, Apple ML Data Platform

(f/m/d) · 4/29/2025

Description

The ADP ML Data Platform team enables future Apple intelligent products by providing Apple engineers with cutting edge ML technologies, large scale compute and data systems specifically designed for machine learning. As a member of the Apple ML Data Platform team, your responsibilities will include: * Prototype and optimize GenAI models, including open-source models, for scalable production use * Build a platform that enables teams to easily configure models, apply tuning strategies (e.g., LoRA/QLoRA), perform quantization, and get models production-ready for scalable deployment * Continuously improve platform capabilities to handle next-gen ML workloads, including foundation models and retrieval-augmented systems * Use ML techniques to drive smarter data workflows - including synthetic data generation, automated labeling, active learning, and data curation * Collaborate across research and engineering teams to accelerate experimentation * Collaborate closely with teams across the stack to enable high-quality, end-to-end ML experiences * Use and extend tools built on modern ML frameworks * Optimize platform components for large-scale ML workloads across distributed systems * Diagnose, fix, improve, and automate complex issues across the entire stack to ensure maximum uptime and performance

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
  • 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 in one or more ML frameworks
  • Experience with containerization and orchestration technologies, such as Docker and Kubernetes.

Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $166,600 and $296,300, 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.

Application

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