Staff Machine Learning Engineer, Automotive Cybersecurity

Qualcomm

Confirmed live today High trust

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$162,000–$243,000 / yr
Posted
40 days ago
Freshness
Confirmed live today
Closes
Mar 16, 2027

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $229k
This role $202k
$148k $291k
below market most similar roles pay here above market

This role pays less than 76% of similar roles. Most pay $202,800–$254,750 — the blue band above. At the midpoint, this role pays about $202k versus about $229k for comparable roles.

Based on 240 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 575 open roles on FindRole.

Listed pay typically runs $147,900–$221,900 across 550 roles with salary data.

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At a glance

TL;DR · Staff Machine Learning Engineer, Automotive Cybersecurity

The Staff Machine Learning Engineer joins the Machine Learning Engineering team to drive AI/ML-based automation across Automotive SoC Cybersecurity and Safety engineering. This role involves building intelligent, scalable solutions to improve engineering productivity and streamline cybersecurity and functional safety workflows throughout the product development lifecycle. You will design and develop automation for document understanding, review automation, and compliance monitoring while building scalable pipelines for security analysis. Key technologies include Python, C++, LLMs, GenAI, agentic AI systems, and retrieval-augmented generation. You will apply these skills to solve complex problems in hardware security, silicon verification, and design automation. The work specifically addresses automotive cybersecurity standards like ISO/SAE 21434 and ISO 26262, focusing on intelligent systems for cross-project reuse and automated regulatory process optimization.

What does a Machine Learning Engineer earn in California?

Median $235750 from 200 postings across 34 companies.

See salary data

What you'll do

  • Design and develop AI/ML-based automation solutions for cybersecurity and functional safety engineering workflows.
  • Build intelligent systems for document understanding, review automation, and engineering productivity.
  • Develop and deploy solutions leveraging LLMs, GenAI, and agentic AI frameworks.
  • Create knowledge automation platforms to support cross-project reuse and decision support.
  • Build scalable, end-to-end automation pipelines spanning multiple engineering domains.
  • Apply AI/ML to security analysis, compliance monitoring, and process optimization.
  • Support the development of hardware security analysis and verification automation tools.

What we're looking for

  • Bachelor's degree in a related field and 4+ years of engineering experience, OR Master's and 3+ years, OR PhD and 2+ years.
  • Strong background in Machine Learning and Artificial Intelligence.
  • Experience with LLMs, GenAI, and agentic AI systems or intelligent automation frameworks.
  • Strong programming skills in Python, C++, or similar languages with solid software engineering fundamentals.
  • Experience building scalable, production-quality ML pipelines, model training workflows, or inference systems.
  • Experience with knowledge systems, semantic search, retrieval-augmented generation (RAG), or workflow orchestration platforms.
  • Familiarity with automotive cybersecurity or functional safety standards (e.g., ISO/SAE 21434, ISO 26262, UNECE WP.29) (preferred).
  • Exposure to hardware security concepts, RTL design, design verification, or silicon validation workflows (preferred).

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