Senior GNSS Systems Engineer: Signal Processing & AI

QUALCOMM, Inc.; Santa Clara (CA); On-site; USD 152,000 - 228,000; Full time

Job summary

Qualcomm Technologies, Inc. leads location and navigation innovation in Santa Clara. This role focuses on GNSS receiver physical layer design, measurement engine subsystems, and cross-functional verification across hardware, firmware, and software teams.

The candidate will design signal processing algorithms, model and verify subsystems, and drive issue resolution with AI-enhanced workflows. Strong academia and industry exposure are valued.

Qualifications

• Knowledge of GNSS systems and receiver design.
• Experience with tracking loops, demodulation, and decoding algorithms.
• Experience with fixed-point modeling for hardware verification.
• Experience with C/C++, Python, MATLAB or Simulink and related tools.
• Experience with ML algorithm design and AI-assisted workflows.

Responsibilities

• Design signal processing algorithms for acquiring, tracking, and measuring GNSS signals.
• Model and verify GNSS Measurement Engine subsystems for pre-product and product designs.
• Support hardware, firmware, software, and RF teams in prototype verification.
• Drive cross-functional issue resolution and optimize system performance.

Skills

GNSS knowledge

Receiver design

Demodulation & decoding

Fixed-point modeling

Machine learning design

C/C++ programming

Python scripting

MATLAB/Simulink

Education

Bachelor's degree in Engineering / Information Systems / CS

Master's degree in Engineering / Information Systems / CS

PhD in Engineering / Information Systems / CS

Tools

RTL hardware concepts

Hardware verification tools

Simulation tools & languages

Job description

Qualcomm Technologies, Inc. leads location and navigation innovation in Santa Clara. This role focuses on GNSS receiver physical layer design, measurement engine subsystems, and cross-functional verification across hardware, firmware, and software teams.

The candidate will design signal processing algorithms, model and verify subsystems, and drive issue resolution with AI-enhanced workflows. Strong academia and industry exposure are valued.