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Staff Machine Learning EngineerApple Inc. • Seattle, Washington, United States
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Staff Machine Learning Engineer

Apple Inc.
  • US
    Seattle, Washington, United States
  • US
    Seattle, Washington, United States
Jetzt Bewerben

Über

Cupertino, California, 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 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.
Responsibilities
As a member of the Apple ML Data Platform team, your responsibilities will include:
Design and build scalable systems for ML data, embeddings, and feature workflows
Develop capabilities that improve experimentation, evaluation, and model performance at scale
Partner with research and product teams to enable rapid GenAI feature development
Drive efficiency, reliability, and automation across inference and AI Ops workflows
Collaborate across infrastructure and product groups to ensure seamless integration and adoption
Prototype and optimize GenAI models, including open‑source models, for scalable production use
Continuously improve platform capabilities to handle next‑gen ML workloads, including foundation models and retrieval‑augmented systems
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
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 the below is preferred:
Proficiency in one or more ML frameworks
Experience with containerization and orchestration technologies, such as Docker and Kubernetes.
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 $212,000 and $318,400, 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.
Apple accepts applications to this posting on an ongoing basis.
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  • Seattle, Washington, United States

Sprachkenntnisse

  • English
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