Senior Robotics Software Engineer – Manipulation & Robot Learning

Robotic Manipulation / Robot Arms / ROS2 / Move It 2 / Motion Planning / Inverse Kinematics / Forward Kinematics / Trajectory Planning / Robot Control / Force Control / Grasping / Insertion / Assembly / Calibration / End-Effector Control / Industrial Robotics / Franka / Universal Robots (UR) / ABB / Flexiv / KUKA / FANUC / Reinforcement Learning / Imitation Learning / Sim-to-Real

Trubot Inc. is a robotics company focused on intelligent inspection robots and automation solutions for data center operations.

We build, deploy, and operate real robotic systems in demanding industrial environments. Our next-generation robotics platform combines robotic manipulation, intelligent perception, robot learning, and autonomous operation to solve real-world automation challenges.

Our mission is to bring advanced robotic manipulation from research into reliable production systems.

We are seeking a Senior Robotics Software Engineer with extensive hands‑on experience developing and deploying software on physical robotic arms
.

This role requires strong expertise in robotic manipulation, ROS2, motion planning, forward and inverse kinematics, trajectory generation, robot control, perception integration, calibration, end‑effector control, and real‑world system debugging.

The ideal candidate has practical experience building robotic manipulation systems on platforms such as Franka, Universal Robots (UR), ABB, Flexiv, KUKA, FANUC, Kinova, or similar industrial robot arms
.

Experience applying machine learning techniques—including reinforcement learning, imitation learning, diffusion policies, or Vision‑Language‑Action (VLA)—to improve robotic manipulation performance is highly desirable.

This is not a simulation‑only or research‑only position. The engineer must be comfortable working directly with physical robots and contributing to real‑world system deployment from day one.

• Design, develop, integrate, and deploy robotic manipulation software on physical robot arms.
• Develop and debug manipulation systems for grasping, insertion, tool use, cable handling, assembly, and other contact‑rich real‑world tasks.
• Implement motion planning, forward and inverse kinematics, trajectory generation, collision checking, calibration, end‑effector integration, force control, and manipulation strategies.
• Integrate perception, planning, control, and hardware interfaces into reliable end‑to‑end robotic systems.
• Deploy, validate, and optimize robotic software on physical robot arms and mobile manipulation platforms.
• Apply machine learning techniques—including reinforcement learning, imitation learning, diffusion policies, and VLA—when they provide measurable improvements to robotic manipulation performance.
• Develop and improve reinforcement learning, imitation learning, behavior cloning, diffusion policies, and other learning‑based methods for robotic manipulation.
• Explore Vision‑Language‑Action (VLA), Embodied AI, and foundation‑model‑based approaches for robotic manipulation.
• Evaluate and improve policy robustness, task success rates, and generalization performance.
• Analyze failure modes and continuously improve manipulation reliability.

• Build and maintain simulation environments using Isaac Sim, Isaac Lab, Mu Jo Co , or similar platforms.
• Develop teleoperation and human demonstration pipelines for data collection.
• Build training datasets, evaluation pipelines, and experiment workflows.
• Support sim‑to‑real transfer and deployment onto physical robotic systems.

• Deploy robotic software onto physical robot arms and production robotic systems.
• Debug and resolve perception, planning, control, and hardware integration issues on…