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Machine Learning Engineer, Foundation Model Services

Apple· Machine Learning Platform Technologies
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Hybrid (Santa Clara, California), Hybrid (Seattle, Washington)$184.7k - $324.8kfull-timePosted 4mo ago

About the role

Foundation Model Services builds frameworks, services and tools powering Apple’s foundation models at scale, enabling low-latency inference across a wide range of Apple products and services. The role focuses on production-grade model serving, optimization for billions of parameters and collaboration with research and product teams to deploy real-time solutions.

Responsibilities

  • Work closely with product teams to build production grade solutions to launch models serving millions of customers in real time.
  • Work alongside Foundation Model Research team to prototype and develop inference for cutting edge model architectures.
  • Build tools to understand bottlenecks in Inference for different hardwares and use cases.

Qualifications

  • 5 year+ industry experience in ML technologies (LLMs, Machine Learning, NLP, Information Retrieval, Statistics).
  • Experience with high throughput services particularly at supercomputing scale.
  • Proficient with running applications on Cloud (AWS / Azure or equivalent) using Kubernetes, Docker etc.
  • Proficient in building and maintaining systems written in modern languages (eg: Golang, python).
  • Bachelor’s degree or higher in Computer Science or related technical field.

Skills

Required:ML framework experienceDeep learning architectures
Nice to have:NVIDIA/TensorRT-LLM related tools

Benefits

  • 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.
  • Discretionary bonuses or commission payments as well as relocation (where eligible).
  • Apple shareholder opportunity through discretionary employee stock programs and Employee Stock Purchase Plan.
Last updated Oct 16, 2026. Interested? Apply on the company site.

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