Sr. / Staff ML Engineer, FM Training Integration - ML Compute

Apple Inc

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$181,100–$318,400 / yr
Posted
23 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $221k
This role $250k
$154k most similar roles pay here $336k

This role pays more than 78% of similar roles. Most pay $193,000–$249,750 — the shaded band above. At the midpoint, this role pays about $250k versus about $221k 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 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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At a glance

TL;DR · Sr. / Staff ML Engineer, FM Training Integration - ML Compute

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As a Senior/Staff Machine Learning Engineer on the ML Compute team at Apple, you will lead the integration of large-scale machine learning workloads with cloud infrastructure, focusing on improving efficiency and reliability. Your daily tasks include optimizing performance across data pipelines, model execution, and distributed systems to enhance throughput and hardware utilization, while also building tooling for observability and debugging. You will collaborate closely with ML engineers, infrastructure experts, and researchers to establish best practices and drive high-quality design reviews. The role requires hands-on experience in Python, major ML frameworks like PyTorch or JAX, and cloud-based distributed systems such as containers and Kubernetes. This position involves working on cutting-edge projects that support the training of foundation models for Apple products, pushing the boundaries of deep learning scalability and efficiency at a massive scale.

Skills

Python PyTorch JAX Docker Kubernetes GPU TPU CI/CD NVIDIA Nsight PyTorch Profiler AWS Azure GCP PostgreSQL MongoDB

What you'll do

  • Own the integration of large-scale model training with cloud infrastructure for reliability.
  • Drive performance optimization across data pipelines, model execution, and distributed systems.
  • Design benchmarks to evaluate model performance and guide optimization efforts.
  • Build tooling for observability, profiling, and debugging ML workloads for visibility.
  • Establish best practices for performance tuning and resource utilization in ML workloads.
  • Lead high-quality design and code reviews to elevate engineering standards across the team.

What we're looking for

  • 5+ years of experience in software engineering, ML infrastructure, or related fields.
  • Hands-on expertise with large-scale machine learning workflows and cloud-based distributed systems.
  • Proficiency in Python and at least one major ML framework like PyTorch or JAX.
  • Experience optimizing performance and reliability of ML workloads on accelerator-based systems.
  • Bachelor’s degree in Computer Science, Engineering, or a related field.

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