Sensor Rendering & Simulation Engineer

Path Robotics; Columbus (OH); On-site; USD 100,000 - 150,000; Full time

Benefits offered by this job

Free lunch

Flexible PTO

Medical, Dental, and Vision insurance

Parental leave: 6 weeks paid plus 6–8–

Maternity leave support

Job summary

Path Robotics is seeking a Software Simulation Engineer to own rendering and simulation of 2D/3D sensors for perception model training. You will build scalable synthetic data pipelines, implement domain randomization, and collaborate with perception teams to meet dataset requirements.

You'll work across Gazebo, NVIDIA Isaac Sim, and Unreal Engine, mentoring others and driving high-fidelity sensor render pipelines grounded in real sensor data.

Qualifications

• Education & Experience: Degree in CS/Robotics/EE plus 3+ years (Experienced) or 5+ years (Senior) in simulation, rendering, or perception.
• Strong Python skills for building production-grade simulation tooling and plugins.
• Hands-on experience with NVIDIA Isaac Sim, Unreal Engine, Blender or Gazebo (Classic/Ignition).
• Solid understanding of Physically Based Rendering (PBR) and experience with 3D assets (URDF, SDF, USD).
• Experience building annotated synthetic dataset generation systems and domain randomization strategies for real-world training.
• Experience with generative image AI (diffusion models) and its application in synthetic data generation.

Responsibilities

• Implement and validate physics-based sensor simulation models (structured light, depth, RGB, stereo, etc.) within platforms such as NVIDIA Isaac Sim, Blender or Unreal Engine, producing outputs that closely match real sensor behavior.
• Build photorealistic scene rendering pipelines that account for sensor placement on the robot end-effector. Emulate robot trajectories with and without physical models. Use accurate material properties to ensure synthetic data supports perception model training.
• Develop synthetic data generation pipelines producing annotated ground-truth (point clouds, depth maps, segmentation masks) at scale.
• Implement domain randomization strategies to improve sim-to-real transfer for downstream perception models.
• Collaborate with perception teams to ensure rendered outputs meet dataset requirements and write high-quality Python code.
• Lead the design and validation of high-fidelity, photorealistic sensor render pipelines grounded in real sensor characterization data and validated against physical measurements.
• Architect the sensor rendering strategy for the Perception team, defining which sensor modalities, material models, and environmental conditions must be simulated.
• Own the sim-to-real validation framework: define benchmarks and go/no-go criteria for synthetic sensor data readiness.
• Drive 3D asset and environment pipeline strategy, including CAD-to-simulation workflows, asset management, material library management, and procedural scene generation across Gazebo, Isaac Sim, and Unreal Engine.
• Define strategy for when and how to use Gazebo, Isaac Sim, or Unreal Engine and build cross-platform workflows.
• Mentor engineers on rendering best practices, physically based material modeling, Gazebo plugin development, and synthetic data methodology.

Skills

Python

Domain randomization

Photorealistic rendering

Perception collaboration

Generative AI

3D data understanding

Education

Bachelor's degree in CS/Robotics/EE

Tools

NVIDIA Isaac Sim

Unreal Engine

Blender

Gazebo

USD

URDF/SDF

CAD-to-render workflows

Job description

Path Robotics is seeking a Software Simulation Engineer to own rendering and simulation of 2D/3D sensors for perception model training. You will build scalable synthetic data pipelines, implement domain randomization, and collaborate with perception teams to meet dataset requirements.

You'll work across Gazebo, NVIDIA Isaac Sim, and Unreal Engine, mentoring others and driving high-fidelity sensor render pipelines grounded in real sensor data.