Senior ML Platform Engineer - Large-Scale AI

Applecart

Sunnyvale (CA)

On-site

USD 180,000 - 260,000

Full time

5 days ago
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Job summary

Apple seeks a Senior ML Platform Engineer to design, build, and optimize large-scale ML systems powering Apple Intelligence with billions of parameters and petabytes of data. You will work on high-performance HPC environments to ensure low-latency, scalable inference across Siri, Search, and Apple services.

You will collaborate with research, infrastructure, and product teams to push state-of-the-art AI forward, prototyping rapid concepts and ensuring rigorous privacy standards throughout

Qualifications

  • 4+ years of experience with LLMs/LMMs or related AI/ML tech.
  • Strong data and model quality understanding; model evaluation experience.
  • Proficient in at least one deep learning framework (PyTorch/TF/JAX).
  • Experience building large-scale ML systems and distributed processing.
  • Excellent communication and independent collaboration skills.

Responsibilities

  • Design, build and maintain large-scale ML systems for Apple platforms.
  • Prototype and validate AI/ML concepts for production deployment.
  • Collaborate with research, infra, and product teams to deliver robust solutions.
  • Optimize models for low latency and high throughput at scale.

Skills

LLMs
LMMs
Computer Vision
PyTorch
TensorFlow
JAX
Distributed Systems
Prototyping
Communication
Cross-functional teamwork

Education

Master's degree or PhD in Computer Science / ML / AI

Tools

PyTorch
TensorFlow
JAX

Job description

Apple seeks a Senior ML Platform Engineer to design, build, and optimize large-scale ML systems powering Apple Intelligence with billions of parameters and petabytes of data. You will work on high-performance HPC environments to ensure low-latency, scalable inference across Siri, Search, and Apple services.

You will collaborate with research, infrastructure, and product teams to push state-of-the-art AI forward, prototyping rapid concepts and ensuring rigorous privacy standards throughout

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