Computer Vision Engineer

As a Computer Vision Engineer, you will be a part of a passionate team whose mission is to bring intelligence to the worlds trucks. The team is focused on building technology to understand driving behavior, identify risk factors, and intelligently suggest coachable events that not only improves the fleet safety and potentially save millions of dollars but also contribute to making the roads safer. You will have a unique opportunity to work with a high caliber and fast-paced team which consists of experienced researchers and engineers in Computer Vision, Machine Learning, Deep Learning, and Robotics with a track record of previous products and top-tier publications.

You will play a critical role in building and improving a technology that will be used by millions of trucks. In this role, you will design and implement complex computer vision systems. You will have the opportunity to build and/or improve algorithms for edge processing, implement cloud services, and integrate them to deliver end-to-end product features. You will also get exposure to large-scale ML infra and scaling that facilitates large amounts of data to train, test, and validate computer vision systems.

What Youll Do:

• Improve the performance of our models and algorithms already in production
• Build and optimize CV/ML algorithms for real-time performance so they can run on our embedded platform i.e. the next-gen AI dashcam
• Write proficient Python and C++ code to build and improve CV algorithms, ML services, training, model compression and porting pipelines
• Convert state-of-the-art research prototypes into reliably working product features
• Collaborate with RnD team working in Computer Vision, Machine Learning, and Robotics, along with ML Platform, Embedded, Backend, and Frontend teams to deliver end-to-end product features
• Solve challenging object detection, segmentation, recognition, and geometric computer vision problems.
• Build automated deployment, validation, and active learning pipelines.

What Were Looking For:

• Bachelors degree in computer science, software engineering, data science, artificial intelligence, or related field.
• Masters or PhD in Computer Vision, Deep Learning, and Machine Learning (preferred)
• 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