Principal Robotics Simulation Architect

Amd

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Austin, TXSanta Clara, CA
Salary
$204,000–$306,000 / yr
Posted
102 days ago
Freshness
Confirmed live yesterday
Closes
Jun 1, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $223k
This role $255k
$151k most similar roles pay here $323k

This role pays more than 74% of similar roles. Most pay $189,737–$256,000 — the shaded band above. At the midpoint, this role pays about $255k versus about $223k for comparable roles.

Based on 240 similar postings.

Employer

About Amd

AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors

Amd currently has 367 open roles on FindRole.

Listed pay typically runs $166,400–$249,600 across 367 roles with salary data.

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At a glance

TL;DR · Principal Robotics Simulation Architect

As a Principal Robotics Simulation Architect, you will join the team to select and advance simulation architecture solutions tailored specifically for robotic systems. You will be responsible for building robust pipelines to transfer learned behaviors, sensor models, and physics parameters between simulation and real-world environments while minimizing the reality gap through domain randomization. Your daily work involves architecting scalable cloud-based infrastructure for distributed training, integrating AI/ML frameworks like PyTorch and TensorFlow into simulation environments, and developing SIL and HIL testing frameworks to validate perception, planning, and control modules. You will utilize tools such as NVIDIA Isaac Sim, Gazebo, MuJoCo, Webots, Unreal Engine, and ROS or ROS2. The role focuses on solving complex hardware-software-simulation interactions by creating digital twins and synthetic data generation for autonomous behavior training in robotic systems.

What you'll do

  • Develop pipelines to transfer learned behaviors and sensor models between simulation and real-world robotic systems.
  • Architect and deploy scalable, high-performance simulation infrastructure on cloud platforms for distributed training.
  • Integrate AI/ML frameworks into simulations to enable reinforcement learning and synthetic data generation.
  • Design and implement SIL testing frameworks to validate perception, planning, and control modules.
  • Develop and maintain HIL testing setups to interface real hardware with simulated environments.
  • Create digital twin models featuring real-time state synchronization and physics calibration.
  • Minimize the reality gap using domain randomization and advanced sensor noise modeling techniques.

What we're looking for

  • Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
  • Proven experience with simulation platforms such as NVIDIA Isaac Sim, Gazebo, MuJoCo, Webots, or Unreal Engine.
  • Experience developing digital twin models for robotic systems including real-time state synchronization and physics calibration.
  • Expertise in designing sim-to-real and real-to-sim pipelines using domain randomization and sensor noise modeling.
  • Proficiency in architecting and deploying scalable, containerized simulation infrastructure on cloud platforms.
  • Experience integrating AI/ML frameworks like PyTorch or TensorFlow into simulation pipelines for training and synthetic data generation.
  • Hands-on experience designing and executing Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) testing workflows.
  • Proven experience with ROS and ROS2 in both simulation and real-world robotic deployments.

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