Staff ML Engineer: Automotive Cybersecurity & AI Automation

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

Job summary

Qualcomm Technologies, Inc. seeks a Staff Machine Learning Engineer to drive AI/ML-based automation across Automotive SoC Cybersecurity and Safety engineering. You will build intelligent systems to improve productivity and automate workflows end-to-end, spanning multiple engineering domains.

You will design, deploy, and scale ML pipelines, leverage LLMs and agentic AI, and contribute to hardware security and design automation initiatives in a fast-paced, cross-functional environment.

Qualifications

• Bachelor's degree with 4+ years hardware/software engineering or related work experience.
• Master's degree with 3+ years or PhD with 2+ years in related fields.
• Experience designing, deploying, and validating ML/AI-based solutions in production or engineering environments.

Responsibilities

• 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.
• Contribute to knowledge automation platforms supporting 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++

Production ML pipelines

Knowledge systems

Semantic search

Automation frameworks

Software engineering fundamentals

Hardware security concepts

ISO/SAE 21434 familiarity

Education

Bachelor's degree in CS/Engineering

Master's degree in CS/Engineering/AI

PhD in CS/Engineering

Job description

Qualcomm Technologies, Inc. seeks a Staff Machine Learning Engineer to drive AI/ML-based automation across Automotive SoC Cybersecurity and Safety engineering. You will build intelligent systems to improve productivity and automate workflows end-to-end, spanning multiple engineering domains.

You will design, deploy, and scale ML pipelines, leverage LLMs and agentic AI, and contribute to hardware security and design automation initiatives in a fast-paced, cross-functional environment.