Staff Engineer- AI/Machine Learning R&D

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Staff – Application/ Customer Engineering

Role Overview

We are looking for a Staff Engineer with strong domain expertise in VLSI/EDA tools and workflows to drive adoption, usability, and reliability of internal GenAI/Agentic AI tools and platform.

This role requires deep hands-on usage, triaging expertise, and customer engineering experience, acting as the bridge between Physical Design Engineers/CAD teams, Software and Systems engineering team.

The ideal candidate has exposure to AI/GenAI systems and can understand and debug workflows involving EDA tools, AI agents, orchestration pipelines, and non-deterministic system behaviors.

Key Responsibilities

• Own end-to-end user support and triage workflows; debug complex EDA environment, configuration and software integration issues