Jobs at Pickle Robot Company

Develop and maintain measurable system requirements for robotic unloading systems, trace product needs through testing, identify verification gaps, and support design documentation and interface definitions. Collaborate with mechanical, electrical, software, product, and test teams to define cross-functional features. Participate in reviews, testing, and robot integration at warehouse and customer sites.

Own end-to-end machine learning for robotic grasping and perception, including problem formulation, large-scale dataset generation and curation, model training, experimentation, evaluation, and verification. Develop vision models using synthetic data, self-supervised labeling, and active learning. Define metrics tied to robot performance, produce deployable model artifacts, conduct code reviews, mentor engineers, and contribute to the perception and grasping roadmap while partnering on runtime integration.

Lead planning and delivery of complex software programs for Pickle's robotics platform. Coordinate cross-functional teams (software, robotics, firmware, hardware), manage risks and dependencies, run planning and release activities, improve processes and tracking, and drive alignment to deliver production-quality robotic software in a fast-paced startup.

Own robotic grasping intelligence by designing bespoke neural networks, building cloud training and evaluation pipelines, deploying models to robot fleets, and improving performance through field telemetry. Develop simulation-first manipulation strategies using robotics concepts including motion planning, kinematics, geometry, and perception. Collaborate with perception and motion-planning engineers while setting technical direction for a small applied ML team.

Develop production-grade robotics perception software for warehouse robots using 3D LiDAR and multisensor data. Own localization, state estimation, obstacle mapping, point-cloud processing, sensor calibration, and integration of machine-learning outputs. Optimize real-time edge-compute pipelines and make system-level architectural decisions for dynamic physical environments.

The Physical AI Architect will design and oversee the implementation of perception, planning, and control systems in robotics, focusing on optimal control and diffusion-based AI techniques while ensuring successful hardware integration.