Renesas is a leading embedded semiconductor solution provider, driven by its purpose 'To Make Our Lives Easier.' As an expert in embedded processing with unmatched quality and system-level know-how, Renesas offers scalable and comprehensive semiconductor solutions for automotive, industrial, infrastructure, and IoT industries. Their broad product portfolio includes High Performance Computing, Embedded Processing, Analog & Connectivity, and Power. With a diverse team of over 22,000 professionals in more than 30 countries, Renesas continuously innovates to enhance user experiences through digitalization, designing sustainable, power-efficient solutions that help people and communities thrive. Renesas Electronics is an equal opportunity and affirmative action employer, committed to fostering a diverse and inclusive work environment.

About the Position

Introduction

Renesas Electronics is seeking a hands-on Senior AI Engineer to develop and deploy edge AI solutions, integrating machine learning with real-world hardware systems. This role focuses on building intelligent applications using sensor data, spanning the entire lifecycle from data collection and model development to deployment on embedded platforms. This position is 100% onsite in Columbia, MD.

Responsibilities

Assemble hardware setups (e.g., physical systems, sensor arrays, embedded boards) and collect data from real-world physical environments for AI model development and validation.
Develop and maintain edge AI-based applications, demos, and solutions combining tiny ML models across various physical hardware settings, including consumer devices, industrial machines, and automotive systems.
Collaborate with internal product and marketing teams to ingest, debug, and analyze data for model development.
Work with other AI and embedded engineers to optimize and deploy AI models suitable for microcontrollers (MCUs) and embedded platforms.
Lead junior engineers and contribute to technical leadership across teams.
Stay current with emerging technologies in AI, embedded ML, and signal processing.

Requirements

Bachelor's (3-4 years) or Master’s degree in Electrical Engineering or a related technical field, and 2-3 years of career experience.
Practical fabrication of prototype systems involving physical, microelectronic, and sensor elements in novel combinations.
Familiarity with design tools, 3D printing, and hands-on electrical and physical assembly.
Broad familiarity with various sensor types, their placement, and applications in embedded systems, including hands-on experience with audio, electrical, accelerometers, and control system signals.
Experience working with large, high-frequency sensor datasets (e.g., audio, electrical, motor control, accel, etc.), including debugging and preprocessing.
Understanding of AI/ML algorithms with experience deploying models on MCUs.
Proficiency in Python, MATLAB, and C, specifically with real-time edge computing and embedded systems experience.
Background in digital signal processing (DSP) for audio and time-series data.
Demonstrated experience leading engineering teams and collaborating effectively across multiple cross-functional groups.
Strong background in physical systems and cross-field experience.
Project management experience and openness to take technical leadership across teams.