Synthetic Data & Teleoperation Engineer (Robotics)

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Position Overview

We are looking for a Synthetic Data & Teleoperation Engineer to develop simulation environments synthetic data pipelines and teleoperation workflows for robotic learning and Vision-Language-Action (VLA) foundation models.

You will help generate realistic training scenarios capture demonstration data for imitation learning and improve the visual fidelity of simulated environments. The role combines robotics simulation 3D environment development teleoperation and dataset engineering to support the development of intelligent robotic systems.

Key Responsibilities

• Develop synthetic data generation pipelines using NVIDIA Isaac Sim and Omniverse for diverse security scenarios including night vision perimeter breaches and adverse weather.

• Build and maintain simulation environments for robotic perception planning and manipulation.

• Configure VR-based teleoperation systems to capture demonstration trajectories for imitation learning.

• Integrate teleoperation workflows using OpenXR and related simulation technologies.

• Manage dataset curation automated labeling and structured demonstration repositories for foundation model training.

• Develop and refine simulation assets using Blender Unreal Engine or similar 3D tools.

• Evaluate photorealism and identify visual discrepancies between simulated and real-world environments.

• Benchmark and reduce Sim-to-Real domain gaps through simulation improvements and data generation techniques.

• Collaborate with AI researchers and robotics engineers to support VLA development and simulation-based training.

Qualifications

• Bachelors or Masters degree in Robotics Computer Science Mechanical Engineering Electrical Engineering Computer Graphics or a related field.

• Approximately 24 years of relevant experience in robotics simulation synthetic data teleoperation or 3D environment development.

• Proficiency in Python and familiarity with C.

• Experience with NVIDIA Isaac Sim Omniverse or comparable robotics simulation platforms.

• Familiarity with USD VR teleoperation OpenXR Blender or Unreal Engine is an advantage.

• Understanding of imitation learning robotic demonstration datasets automated labeling or synthetic data generation.

• Knowledge of domain randomization photorealistic simulation or Sim-to-Real evaluation is a plus.

• Strong problem-solving skills and the ability to work across simulation data and robotics systems.

Why Join

• Contribute to emerging technologies in robotics simulation and embodied AI.

• Build synthetic environments and demonstration pipelines for advanced robotic learning.

• Work with AI researchers and robotics engineers on challenging applied R&D projects.

• Help bridge the gap between simulated training and real-world robotic performance.