Electronic Logging Devices • Fleet Management • Vehicle GPS Tracking • Driver Vehicle Inspection Reports • IFTA Reporting
1001 - 5000
November 9
Electronic Logging Devices • Fleet Management • Vehicle GPS Tracking • Driver Vehicle Inspection Reports • IFTA Reporting
1001 - 5000
• Who we are: • Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. • Motive serves more than 120,000 customers – from Fortune 500 enterprises to small businesses. • About the role: As a Computer Vision Engineer, you will bring intelligence to the world’s trucks. • You will play a critical role in building and improving technology that will be used by millions of trucks. • What You’ll Do: Improve the performance of our models and algorithms already in production. • Build and optimize CV/ML algorithms for real-time performance. • Write proficient Python and C++ code to build and improve CV algorithms. • Collaborate with RnD team working in Computer Vision, Machine Learning, and Robotics. • Solve challenging object detection, segmentation, recognition, and geometric computer vision problems.
• At least 5+ years of algorithm development experience in the area of Computer Vision, Deep Learning, and Machine Learning. • Candidates with Masters in Computer Vision, Deep Learning, and Machine Learning and 2+ years of relevant experience. • Fresh PhD candidates are encouraged to apply. • Solid mathematical foundation in Computer Vision, Deep Learning, Machine Learning, and optimization approaches. • Hands-on experience in training framework and tools (TensorFlow | Pytorch | Caffe) • Strong experience in Python or C++ • Hands-on experience in building embedded algorithms and applications • Experience in the following tools and technologies is a plus: AWS (SageMaker, Lambda, EC2, S3, RDS), CI/CD, Terraform, Docker, and Kubernetes. • Prior experience with Eigen library and RTOS is a strong plus.
Apply NowOctober 9
Lead design and deployment of AI computer vision solutions for government.