Teams at Treeswift

Develop and maintain embedded software for field robotics, including real-time capabilities, diagnostics, data pipelines, operating system upgrades, fleet deployments, sensor integration, and customer issue resolution. Optimize software for unreliable connectivity and commercially distributed hardware. Collaborate across hardware, robotics, cloud, and field teams while supporting device security, testing, documentation, and scalable operations.

Lead Treeswift’s machine learning team and technical direction, improving model quality, training and inference pipelines, MLOps, and edge deployment. Develop models using sensor data such as images, video, LiDAR, and point clouds. Establish dataset curation, evaluation, and feedback processes, collaborate with software, robotics, hardware, and product teams, and mentor engineers across distributed offices.

Coordinate interviews across hiring teams, manage candidate communication and interview logistics, maintain accurate ATS records, support offers and sourcing, and improve recruiting workflows. The role partners with recruiters and hiring managers to keep searches organized and moving forward while strengthening candidate experience. It requires strong organization, communication, follow-through, and comfort working in a fast-paced NYC startup environment.