Machine Learning Engineer, Platform Architecture

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$150,400–$277,600 / yr
Posted
3 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $208k
This role $214k
$135k most similar roles pay here $293k

This role pays more than 55% of similar roles. Most pay $174,550–$242,000 — the shaded band above. At the midpoint, this role pays about $214k versus about $208k 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 2299 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1870 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer, Platform Architecture

As a Machine Learning Engineer, Platform Architecture, you will join the Platform Architecture group to work at the intersection of machine learning applications and silicon architecture. You will collaborate with cross-functional teams to design how hardware and software function as a unified system. Your daily responsibilities include creating optimized implementations of machine learning workloads on Apple silicon, including the Neural Engine, GPU, and CPU. You will develop performance models and simulations for future hardware, conduct performance studies to validate architectural decisions, and analyze trade-offs for emerging techniques. The role requires proficiency in C/C++ or Python, knowledge of computer architecture fundamentals, and experience with ML frameworks like PyTorch. You will also utilize skills in compiler technologies and algorithm prototyping to ensure machine learning workloads run efficiently on system-on-a-chip architectures.

What does a Machine Learning Engineer earn in California?

Median $247075 from 176 postings across 30 companies.

See salary data

What you'll do

  • Create optimized implementations of ML workloads on Neural Engine, GPU, and CPU hardware.
  • Develop performance models and simulations for future SoC and IP architectures.
  • Conduct performance studies to inform and validate architectural decisions.
  • Analyze system architecture trade-offs for emerging machine learning techniques.
  • Prototype algorithms on various processing units to analyze performance metrics.
  • Create high-level complexity models for machine learning workloads.
  • Communicate technical findings regarding workload efficiency to software and algorithm teams.

What we're looking for

  • Ability to program in C/C++ and/or Python.
  • Knowledge of computer architecture fundamentals.
  • Domain knowledge in at least one hardware IP, such as ML accelerators, GPUs, CPUs, or similar.
  • MS or PhD in EE/CE/CS or related field, or 3+ years of relevant experience (preferred).
  • Experience with ML frameworks and efficient implementations of machine learning algorithms (preferred).
  • Experience optimizing and deploying ML models or runtime frameworks in production environments (preferred).
  • Experience creating SoC or IP performance models/simulations (preferred).
  • Bachelor’s degree.

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