Staff ML Engineer - AI Automation for Automotive Security

Qualcomm; San Diego (CA); On-site; USD 158,000 - 238,000; Full time

Job summary

Qualcomm Technologies, Inc. in San Diego, CA seeks a Staff Machine Learning Engineer to drive AI/ML-based automation across Automotive SoC Cybersecurity and Safety engineering.

You will build intelligent, scalable solutions to improve engineering productivity and automate workflows throughout the product development lifecycle. The role spans AI-assisted engineering tools, automated compliance, and future capabilities in hardware security, silicon verification, and AI-driven design automation,

Qualifications

• Bachelor's, Master's, or PhD in CS/Engineering or related field with 4+ years hardware/software/systems experience.
• OR Master's degree with 3+ years experience.
• OR PhD with 2+ years experience.

Responsibilities

• Design and develop AI/ML-based automation solutions for cybersecurity and functional safety workflows.
• Build intelligent systems for document understanding and engineering productivity.
• Develop and deploy solutions leveraging LLMs, GenAI, and agentic AI frameworks.
• Contribute to knowledge automation platforms for 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.

Skills

Machine Learning

GenAI / LLMs

Python

C++

ML pipelines

Knowledge systems

Automotive cybersecurity

ISO/SAE 21434

RTL design

Design verification

Education

Bachelor's degree in CS/Engineering/IS

Master's degree in CS/Engineering/IS

PhD in CS/Engineering/IS

Tools

Python

C++

Model training workflows

RAG / knowledge graphs

Cybersecurity tooling

Job description

Qualcomm Technologies, Inc. in San Diego, CA seeks a Staff Machine Learning Engineer to drive AI/ML-based automation across Automotive SoC Cybersecurity and Safety engineering.

You will build intelligent, scalable solutions to improve engineering productivity and automate workflows throughout the product development lifecycle. The role spans AI-assisted engineering tools, automated compliance, and future capabilities in hardware security, silicon verification, and AI-driven design automation,