Synthetic Data, Teleoperation Engineer – Robotics

Asiacruit

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

Posted 10/26/2026contractSeoul • South KoreaJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing synthetic data generation pipelines and simulation environments for robotics, utilizing tools such as NVIDIA Isaac Sim and Omniverse. Proficient in Python programming and familiar with teleoperation systems, 3D modeling, and simulation technologies to enhance robotic perception and training.

Highest-signal resume keywords

NVIDIA Isaac SimOmniversePython ProgrammingRobotics SimulationTeleoperation Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Synthetic Data Generation3D Environment DevelopmentAutomated LabelingImitation LearningDomain Randomization

Soft Skills

Problem-Solving

Tools & Technologies

BlenderUnreal EngineOpenXRUSDVR Teleoperation

Industry Keywords

RoboticsSimulationData CurationPhotorealismSim-to-Real Evaluation

Tech Stack

Tools & technologies

PythonUnreal EngineC++

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

Bachelor's or Master's degree in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, Computer Graphics, or a related field
Approximately 2–4 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

Benefits

Comp & perks

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
Hybrid work arrangement