Synthetic Data & Teleoperation Engineer (Robotics)

About Asiacruit
At Asiacruit, we connect top talent with forward-thinking organizations across industries. Our mission is to help businesses grow through smart, strategic, and people-focused solutions. We support companies by providing high-quality talent for local and global markets.
Position Overview
We are looking for a Synthetic Data & Teleoperation Engineer to build simulation environments, synthetic data pipelines, and teleoperation systems that support the development of Vision-Language-Action (VLA) models and robotic learning.
You will create realistic virtual environments for diverse security scenarios, develop systems for capturing robotic demonstrations, and manage datasets used to train and evaluate AI models. This role combines robotics simulation, 3D environment development, teleoperation hardware, and data engineering to help bridge the gap between simulated training and real-world robotic applications.
Key Responsibilities
Build synthetic data generation pipelines using NVIDIA Isaac Sim and Omniverse for diverse scenarios, including night vision, perimeter breaches, and adverse weather conditions.
Develop and maintain simulation environments that support robotic perception, planning, and manipulation tasks.
Design, configure, and maintain VR-based teleoperation systems and hardware setups to capture high-quality demonstration trajectories for imitation learning.
Integrate teleoperation interfaces and robotics simulation workflows using OpenXR and related technologies.
Develop and maintain dataset curation, automated labeling, and data processing pipelines for robotic foundation model training.
Organize and maintain structured, tokenized repositories of robotic demonstrations for training and evaluation.
Use tools such as Blender and Unreal Engine to develop and refine realistic 3D environments and simulation assets.
Evaluate simulation realism and identify visual discrepancies between simulated environments and real-world conditions.
Benchmark and reduce Sim-to-Real domain gaps to improve the reliability of models trained on synthetic data.
Collaborate with AI researchers and robotics engineers to support VLA model development, imitation learning, and simulation-based experimentation.
Qualifications
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 generation, teleoperation, 3D environment development, or related areas.
Proficiency in Python and familiarity with C++.
Hands-on experience with NVIDIA Isaac Sim, Omniverse, or other robotics simulation platforms.
Understanding of USD (Universal Scene Description) and simulation asset workflows.
Experience with VR-based teleoperation, OpenXR, or hardware interfaces is an advantage.
Familiarity with Blender, Unreal Engine, or other 3D content creation tools.
Understanding of robotic demonstration collection, imitation learning, or robotics dataset preparation.
Knowledge of synthetic data generation, automated labeling, domain randomization, or Sim-to-Real evaluation is a plus.
Strong troubleshooting skills and the ability to build practical simulation and data pipelines.
Why Join?
Work at the intersection of robotics simulation, synthetic data, and embodied AI.
Build virtual environments and teleoperation systems that support real-world robotic learning.
Contribute to the development of advanced AI systems using simulation-driven training and evaluation.
Collaborate with multidisciplinary teams working on robotics, foundation models, and intelligent perception.

Work arrangement
No