Computer Vision Engineer

Role overview Develop computer vision algorithms and production pipelines for tasks such as localization, mapping, and detection. The role combines machine learning and image or video processing with the engineering work needed to make systems robust at scale, in collaboration with hardware specialists.

Responsibilities - Design, implement, and optimize computer vision and machine learning algorithms. - Build and maintain scalable systems for processing large image datasets and vision workloads. - Develop techniques for video processing and image recognition. - Integrate and tune vision pipelines alongside hardware engineers.

Requirements - At least three years of experience with production computer vision systems. - Strong knowledge of computer vision, deep learning, and machine learning methods. - Programming proficiency in Python; C++ is useful. - Experience with machine learning frameworks such as PyTorch or TensorFlow and vision libraries such as OpenCV. - Bachelor’s or master’s degree in computer science, robotics, or a related field. - Strong analytical problem-solving, communication, and teamwork skills.

Nice to have - Doctoral degree or five or more years of production computer vision experience. - Experience deploying real-time systems on embedded or robotic platforms.

Benefits and work setup - The listing states compensation of $155,000–$210,000 USD plus equity. - Applicants must already be authorized to work in the United States, Canada, or the United Kingdom, now and in the future; sponsorship is unavailable.