Software Engineer, ML Performance
Serve RoboticsFull Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Candidates should have hands-on hardware experience with embedded devices like NVIDIA Jetson, industrial cameras, or similar hardware in field deployments. Familiarity with computer vision inference pipelines, such as Roboflow, is also required. The role demands a self-starter attitude with the ability to operate autonomously in the field and determine when to escalate issues.
The Edge Engineer will assemble, configure, and test Roboflow edge devices, including Jetson devices, servers, cameras, and sensors. They will build relationships with hardware partners, manage hardware inventory, and lead on-site device installations, hardware bring-up, and system validation. Responsibilities also include performing physical mounting, sensor alignment, cabling, and PoE configuration, ensuring proper connectivity, and supporting customers in field troubleshooting of cameras, inference pipelines, and data uploads. The role involves managing network setup on Linux-based edge devices, contributing to internal tooling for deployment efficiency, and creating technical documentation. Travel up to 75% to customer locations is expected.
Platform for creating and deploying AI models
Roboflow offers a platform for engineers to create, train, and deploy machine learning models using their own images and videos. The platform features an auto-annotate API for efficient data labeling, along with tools for preprocessing and augmenting image data. Roboflow distinguishes itself from competitors by providing project management tools that enhance team collaboration on AI projects. The company's goal is to simplify the AI development process for a diverse range of clients, from individual engineers to large organizations.