Autonomous truck unloading robots powered by computer vision and generative AI
Pickle Robot builds autonomous systems that unload trucks, trailers, and containers at human-scale performance using computer vision, generative AI, and industrial robotics. The tech stack—ROS, Isaac Sim, Gazebo, GCP, and Terraform—reflects a robotics-first engineering organization focused on simulation-to-production workflows. Active projects cluster around scaling multi-robot deployment and warehouse automation platforms, with hiring concentrated in senior and mid-level engineering roles, suggesting the company is moving from prototype-stage robotics toward production-grade distributed systems.
Pickle Robot designs and operates autonomous unloading robots for supply chain and logistics operations. Founded in 2018 and based in Boston, the company employs 51–200 people, with engineering and operations as the dominant functions. The product roadmap spans hardware integration, motion planning software, cloud orchestration (Terraform/GCP), and test automation for warehouse-scale deployments. Customers are logistics and supply chain operators managing truck and container unload workflows.
Core robotics: ROS, Isaac Sim, Gazebo. Backend/infra: Python, Java, C++, GCP, Terraform, Docker, Jenkins. Testing: Playwright, Selenium, Appium, TestNG, TestRail. Design/ops: Onshape, Jira, Confluence, Tableau, NetSuite.
Hardware integration, scalable multi-robot deployment, next-generation robotics platform, motion planning software, cloud architecture design with Terraform, and warehouse automation test automation.
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