Apple Silicon GPU Driver Engineer, Graphics, Game and ML

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$147,400–$220,900 / yr
Posted
56 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $213k
This role $184k
$133k most similar roles pay here $278k

This role pays less than 75% of similar roles. Most pay $188,131–$236,900 — the shaded band above. At the midpoint, this role pays about $184k versus about $213k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Apple Silicon GPU Driver Engineer, Graphics, Game and ML

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As a senior/principal engineer on Apple's GGML team, you will lead the design and implementation of GPU scheduling mechanisms for server-side ML acceleration, impacting performance and power efficiency across all Apple devices using Apple Silicon GPUs. Your day-to-day responsibilities include architecting the GPU driver scheduling layer to optimize ML/LLM workloads, designing parallelism strategies that scale from single GPUs to multi-node clusters, and building synchronization and communication primitives with RDMA technologies. You will collaborate closely with hardware and software teams to co-design next-generation GPU features, contribute to API design for higher layers of the ML stack, and drive performance analysis and optimization for distributed systems. This role requires expertise in C/C++, operating systems, scheduling policies, distributed systems, and parallel computing architectures, as well as experience with GPU programming and inter-node communication technologies like InfiniBand and RDMA.

Skills

C C++ CUDA ROCm Metal Python Distributed systems Parallel computing RDMA NCCL InfiniBand Linux GPU programming ML frameworks CI/CD

What you'll do

  • Design and implement GPU driver scheduling features optimized for ML/LLM workloads.
  • Develop scheduling strategies to achieve efficient parallelism across multiple GPUs.
  • Co-design next-generation GPU scheduling primitives with hardware teams.
  • Implement multi-GPU communication using RDMA technologies, integrating with SoC.
  • Contribute to the design of APIs exposing scheduling control in the ML stack.
  • Drive performance analysis and optimization for distributed ML workloads.

What we're looking for

  • Strong experience in operating systems and scheduling policies
  • Expertise in systems programming using C or C++
  • Deep understanding of distributed systems and parallel computing architectures
  • Experience with GPU programming (CUDA/ROCm/Metal) and high-performance computing
  • Knowledge of inter-node communication technologies like InfiniBand, RDMA, NCCL
  • Technical BS/MS degree or equivalent experience in computer science/engineering
  • Understanding of systems architecture, compilers, and algorithms

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