Embodied AI Real2Sim Engineer

Roboticsconnected; Santa Clara (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Health insurance

Vision care

Dental coverage

401(k)

Paid holidays

PTO (Paid Time Off)

Sick leave

Job summary

Roboticsconnected in Santa Clara, CA is seeking a skilled Real2Sim engineer to lead end-to-end digital-to-simulation workflows, reconstructing visuals and physical properties for robot assets and scenes. You will calibrate contact, friction, and inertia, configure USD/URDF/MJCF assets, and build automated tools for data processing, validation, and sim-real alignment.

Collaborate across perception, robot learning and hardware teams to design benchmarks, reduce sim-to-real gaps, and deliver robust

Qualifications

• Proficiency in Real2Sim pipelines and asset standards.
• Experience with USD / URDF / MJCF and animation/rigid-body resources.
• Familiarity with camera calibration, 3D reconstruction, and point cloud processing.

Responsibilities

• Own end-to-end Real2Sim workflow across simulation platforms to align dynamic and perceptual behaviors.
• Create and validate SimReady assets with proper joints, mass/inertia, and labels.
• Process real-world data: calibration, meshes, textures; export assets for engines.
• Develop tools for calibration, data processing and asset validation.
• Collaborate across perception, robot learning, simulation, and hardware teams to improve calibration protocols.
• Design excitation trajectories for system identification and collect dynamic data.

Skills

Real2Sim pipelines

Python / C++

USD / URDF / MJCF

3D reconstruction

camera calibration

rigid-body dynamics

Tools

Isaac Sim

MuJoCo

Genesis

Blender

Job description

Core Objective: Build the digital pipeline from the real world to simulation space. Reconstruct and calibrate visual and physical properties of robots, objects and scenes, and deliver SimReady interactive assets to reduce the sim-to-real gap, supporting algorithm training, simulation evaluation and policy transfer to real hardware.

RESPONSIBILITIES

• Own the end-to-end Real2Sim workflow based on Isaac Sim, MuJoCo, Genesis, Blender and other simulation platforms, including 3D reconstruction, appearance reconstruction, dynamic identification, calibration of contact, friction and inertia parameters, to align dynamic and perceptual behaviors between simulation and real robots.
• Create, validate and iterate SimReady assets following USD / URDF / MJCF standards. Configure joints, collision shapes, mass/inertia, joint limits, semantic labels and affordance properties for robots and interactive objects, to achieve physical parameter calibration of simulation assets, ensuring stable usability in simulation training.
• Process multi-modal real-world captured data: camera calibration, point cloud & mesh processing, texture and PBR material calibration. Leverage 3DGS / NeRF and related reconstruction methods to digitize real scenes and export assets compatible with simulation engines.
• Develop automated tools for calibration, data processing and asset quality inspection. Document asset specifications, calibration workflows and evaluation metrics to improve pipeline throughput and sim-real alignment accuracy.
• Collaborate with perception, robot learning, simulation engine and hardware teams, design quantitative sim-real benchmark experiments, identify simulation bias, and continuously improve calibration protocols and asset standards for closed-loop data iteration.
• Design excitation trajectories for robot system identification, collect time-series dynamic data from physical robots, calibrate and reproduce non-ideal dynamic behaviors including nonlinear joint friction and transmission backlash.

REQUIREMENTS

MUST-HAVE

• Proficiency in at least one simulation/graphics tool such as Isaac Sim, MuJoCo, Genesis or Blender, with solid understanding of computer graphics and rigid-body dynamics. Familiar with physics simulation engines such as PhysX and Newton.
• Hands-on experience with Real2Sim pipelines and SimReady asset standards; capable of independently building, configuring and validating robot or object assets including joint setup and physical property tuning.
• Knowledge of 3D reconstruction, camera imaging, point cloud processing and camera calibration; fundamental understanding of system identification, parameter calibration and contact/friction models for physical simulation. Familiar with PBR rendering and material creation.
• Ability to decompose requirements, implement technical solutions, run comparative experiments and root-cause sim-real mismatches from visual reconstruction or physical simulation.
• Capable of designing dynamic system identification experiments, analyzing measured hardware data, and quantifying sim-real errors introduced by nonlinear dynamics.

NICE-TO-HAVE

• Proven track record delivering Real2Sim projects, especially for robotic arms, dexterous hands or humanoid robots.
• Deep familiarity with USD / URDF / MJCF, experience building asset libraries and automated asset validation pipelines.
• Skilled in Python / C++ for calibration scripts, engine extensions and data processing tools.
• Experience with 3DGS, NeRF, PBR reconstruction and photogrammetry.
• Background in system identification, excitation trajectory design, dynamic parameter estimation and contact model tuning.
• Understanding of Sim2Real, reinforcement learning and embodied AI closed-loop systems.
• Experience with motion capture, multi-sensor calibration and real robot hardware experiments.
• Familiar with nonlinear friction models such as LuGre and Stribeck, with experience modeling and tuning joint hysteresis and backlash.

DEFAULT BENEFITS

• Health insurance
• Vision care
• Dental coverage
• 401(k)
• Paid holidays
• PTO (Paid Time Off)
• Sick leave