Sr AI Engineer

Renesas Electronics•Columbia, MD

1d•$84,000 - $105,000•Onsite

About The Position

We are seeking a hands-on Senior AI Engineer to build and deploy edge AI solutions that integrate machine learning with real-world hardware systems. This role focuses on developing intelligent applications using sensor data, working across the full lifecycle from data collection and model development to deployment on embedded platforms.

Requirements

Bachelors (3-4 years) Master’s Electrical Engineering or related technical field, and 2-3 years career experience.
Practical fabrication of prototype systems that include physical, microelectronic, and sensor elements in novel combinations, including familiarity with design tools, 3D printing, and hands-on electrical and physical assembly
Broad familiarity with types of sensors and 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 including experience with real time edge computing and embedded systems.
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, cross-field exp
Lead junior engineers and communicate with different teams, have project management exp, open to take technical leadership across teams.

Responsibilities

Assemble hardware setups (e.g., physical systems, sensor arrays, embedded boards) and collect data from real-world physical environments to support AI model development and validation.
Develop and maintain edge AI based applications, demos and solutions combining tiny ML models in a wide variety of physical hardware settings, including consumer devices, industrial machines and automotive.
Collaborate with internal product and marketing teams to ingest, debug, and analyze their 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.