Algorithm Developer: Multi-Modal Sensor Calibration at LeddarTech - Envision the road ahead!

LeddarTech, specializing in AI-based low-level sensor fusion and perception software, is seeking an Algorithm Developer to join their team. The company's solutions enable the deployment of advanced driver assistance systems (ADAS), autonomous driving (AD) and parking applications. LeddarVision™, their automotive-grade software, generates precise 3D environmental models for improved decision making and navigation safety.

The Algorithm Developer will focus on developing algorithms for automotive-grade sensor calibrations. This role involves conducting literature surveys, proof of concepts, and full product-oriented algorithms research, developing test metrics and evaluation methods, and collaborating with the application engineering team.

Role Involves:

• Developing algorithms for automotive grade sensor calibrations
• Developing calibration algorithms for Cameras, Radars, Lidars, IMUs
• Conducting literature surveys and proof of concepts
• Developing test metrics and evaluation methods
• Collaborating with application engineering team
• Performing design reviews and knowledge sharing

Requirements:

• PhD or M.Sc. in Electrical Engineers / Computer Science / Physics from top tier universities
• At least 3 years of proven experience in algorithm development and innovations in Computer Vision
• Camera intrinsic and extrinsic calibration experience
• Ability to take full ownership of R&D process
• Python experience
• Deep Learning experience - advantage
• Sensors Fusion experience - advantage

LeddarTech offers:

• Many positions in the organization allow for flexible and hybrid work hours.
• Global collaborative multi-disciplinary teams
• Opportunities to attend seminars, trainings, and conferences to enhance your skills.
• Employee Assistance Program.
• Free onsite parking.
• Public transit accessibility.
• Comprehensive compensation package including short term incentives and long term incentives.
• Generous paid time off.