SoC Machine Learning Design Engineer

Apple Inc

Confirmed live today Trusted

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$150,400–$277,600 / yr
Posted
21 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $211k
This role $214k
$135k $293k
below market most similar roles pay here above market

This role pays more than 53% of similar roles. Most pay $179,231–$242,062 — the blue band above. At the midpoint, this role pays about $214k versus about $211k 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 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · SoC Machine Learning Design Engineer

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The SoC Machine Learning Design Engineer joins a hands-on development team focused on building efficient application processors for next-generation products. In this role, you will develop generative AI and machine learning solutions to optimize RTL design, verification, and power, performance, and area efforts. You will collaborate with multi-functional teams and the AIML organization to tailor solutions to specific domain needs. Key technical requirements include practical knowledge of generative AI, RAG systems, embedding models, and deep neural networks. You should be proficient with frameworks like PyTorch, TensorFlow, JAX, or MLX, and possess a solid math background in algorithms and data structures. Experience with hardware description languages like Verilog, SystemVerilog, or VHDL, along with front-end tools for static timing analysis and UVM testbenches, is also highly valued.

Skills

Machine Learning Generative AI PyTorch TensorFlow JAX MLX RAG Verilog SystemVerilog VHDL UVM Static Timing Analysis CDC RDC Reinforcement Learning Deep Neural Networks Data Structures Algorithms

What you'll do

  • Develop generative AI and machine learning solutions to optimize RTL Design, Verification, and Power/Performance/Area efforts.
  • Implement machine learning methodologies to improve productivity and optimizations across SoC design functions.
  • Tailor machine learning solutions to meet domain-specific needs of internal multi-functional teams.
  • Design and implement AI evaluation and testing proficiency, including test suites and human evaluation frameworks.
  • Develop generative AI pipelines and RAG systems including embedding models and retrieval strategies.
  • Monitor and integrate emerging technologies in machine learning and chip design to maintain state-of-the-art solutions.
  • Apply deep learning frameworks like PyTorch, TensorFlow, JAX, or MLX to hardware design problems.

What we're looking for

  • Bachelor's degree and a minimum of 3 years of relevant industry experience.
  • Practical experience and knowledge of generative AI and modern machine learning methods (preferred).
  • Experience with RAG systems, generative AI pipeline development, AI evaluation, or AI coding assistants (preferred).
  • Experience with deep neural networks and reinforcement learning (preferred).
  • Solid math background and understanding of algorithms and data structures.
  • Experience with deep learning frameworks such as PyTorch, TensorFlow, JAX, or MLX.
  • Experience with hardware description languages like Verilog, SystemVerilog, or VHDL.
  • Experience with chip design, verification front-end flows, or UVM testbenches (preferred).

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