Company Description

Correct-AI is a company located in Edmonton, AB that specializes in providing platform solutions for clients in need of sophisticated and automated optical navigation techniques for their vehicles. Our vision guidance systems utilize computer vision, robotics, and artificial intelligence technologies to enhance equipment performance while ensuring safety.

Role Description

This is a full-time on-site role for a Computer Vision Machine Learning Engineer. The role involves working on a day-to-day basis to develop and implement computer vision and machine learning technologies for vision guidance systems. The engineer will be responsible for designing and optimizing algorithms, conducting pattern recognition and analysis, and utilizing neural networks and statistics to improve system performance.

Key Responsibilities:

Design, develop, and implement computer vision algorithms for real-time object detection, tracking, and classification.
Work on sensor fusion techniques to integrate data from multiple sources (cameras, LiDAR, GNSS, etc.) for accurate environment perception.
Develop and optimize algorithms for key tasks such as vehicle localization, path planning, and obstacle avoidance.
Collaborate with cross-functional teams to integrate machine learning models into the overall system architecture.
Conduct rigorous testing and validation of computer vision models to ensure reliability and robustness in diverse conditions.
Stay abreast of the latest developments in AI, machine learning, and computer vision to improve system performance continuously.

Required Skills and Qualifications:

A degree in Computer Science, Electrical Engineering, Robotics, or a related field, with a strong focus on computer vision and machine learning.
A minimum of 5 years of hands-on experience in designing and implementing advanced computer vision algorithms, preferably in the context of autonomous driving or robotics.
Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and computer vision libraries (e.g., OpenCV, MediaPipe).
Strong software programming skills in C++, Python, or other relevant languages.
Familiarity with sensor technologies and hardware used in autonomous vehicles, such as GNSS, IMU, cameras, LiDAR, and radar.
Excellent problem-solving abilities and a creative approach to tackling complex challenges.
Strong communication skills and the ability to work collaboratively in a fast-paced, interdisciplinary team.

Preferred Qualifications:

Experience with deep learning techniques for video and image analysis, particularly in the context of autonomous systems.
Knowledge of SLAM (Simultaneous Localization and Mapping) and its applications in autonomous navigation.
Proficiency in simulation software (e.g., Gazebo, LGSVL, Webots, V-REP, or Unity) for testing and validating computer vision algorithms in virtual environments.
Familiarity with cross-device communication technologies and protocols (e.g., CANBUS, MQTT, WebSocket, ROS, gRPC) for seamless integration of various system components.
Prior involvement in projects related to autonomous driving, robotics, or a similar field, with a demonstrated ability to apply machine learning in practical, real-world situations.
Proficiency in reinforcement learning techniques and algorithms, particularly in the context of autonomous systems.

What We Offer:

The opportunity to be a part of a groundbreaking project with the potential to transform urban mobility.
A collaborative and inclusive work environment where innovation and creativity are valued.
Competitive salary and benefits package, including health, dental, and vision insurance and paid time off.
Continuous learning and professional development opportunities in a rapidly evolving field.

Correct-AI jobs

Computer Vision Machine Learning Engineer