Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

valeo.wd3.myworkdayjobs.com

Tech stack

Big Data Hardware-In-The-Loop Simulation Python (Programming Language) MATLAB Signal Processing Software Requirements Analysis

Job description

• Algorithm Development & Optimization: Design, simulate, and implement advanced interference mitigation techniques (e.g., signal reconstruction, spatial filtering, frequency hopping, or adaptive thresholding) to ensure robust detection in dense environments.
• Root Cause Analysis: Lead deep-dive investigations into current project “warning flags” to identify specific interference patterns (mutual interference, environmental noise) causing performance degradation.
• Performance Benchmarking: Evaluate Valeo’s interference robustness against competitors and define the technical roadmap required to achieve “best-in-class” status for upcoming RFQs.
• Project Support & Troubleshooting: Act as the Tier-3 expert for running projects, providing rapid solutions for interference-related issues identified during vehicle testing or customer validation.
• Standardization & IP: Drive the creation of Valeo internal standards for interference testing and contribute to the company’s patent portfolio to protect unique mitigation IP.
• Validation Framework: Define specific test scenarios and KPIs for “Crowded Radar” environments to be used in HIL (Hardware-in-the-Loop) and vehicle-level testing.

Requirements

• Education: Master’s degree or PhD in Signal Processing, Communication Engineering, or Physics.
• Interference Expertise: Deep theoretical and practical knowledge of radar interference mechanisms (e.g., noise floor rise, ghost targets, and signal masking) in FMCW and PMCW systems.
• Signal Processing Mastery: Advanced skills in digital signal processing, specifically in the areas of non-stationary signal analysis and statistical filtering.
• Tools: Expert proficiency in MATLAB/Python for algorithm modeling and large-scale data analysis of raw radar returns.
• Problem-Solving: Proven ability to translate complex physical phenomena into mathematical models and implementable software requirements.

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