As an AI Robotics Research Engineer, you will design, develop, and implement robotic foundation models and reinforcement learning algorithms for multi-agent systems. You will collaborate with a cross-functional team to train models, develop data pipelines, and support production systems, contributing to the advancement of autonomous robotics solutions.

As a Product & Test Engineer at Nimble, you'll drive robotics products by analyzing data for feature improvements, overseeing product lifecycle from concept to deployment, and documenting system integrations and test plans, working closely with cross-functional teams.

As a Robotics Engineer at Nimble, you will design, develop, and implement robotic systems focusing on perception, motion planning, and control. You will work with a cross-functional team to prototype, test, and deploy algorithms, ensuring optimal performance and reliability of robotic software.

The Operations Supervisor oversees the daily operations of the warehouse, focusing on achieving production goals and developing staff. Responsibilities include managing shipping/receiving schedules, supervising personnel, ensuring equipment efficiency, and coordinating with management on maintenance and operational improvements. Communication with the team and reporting on daily objectives are also key duties.

The Operations Supervisor at Nimble is responsible for overseeing daily production, training associates, and making recommendations for system improvements in a robotics and AI startup environment. This role involves managing warehouse operations, coordinating shipments, equipment maintenance, and employee development activities.

The Quality Assurance Specialist at Nimble is responsible for ensuring the quality and reliability of robotics and AI solutions in logistics. This role includes testing, identifying defects, and collaborating with development teams to ensure product performance and compliance with specifications.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, manage data lakes, develop ETL processes, and ensure data integrity while collaborating with stakeholders to support business objectives.