Software Engineer, Robotics Platform

Radical AI; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Radical AI in New York develops a self-driving lab platform that accelerates robotics research. We are seeking a Software Engineer, Robotics Platform to architect simulation and robotics infrastructure used to test and deploy intelligent robotic systems at high speed.

You will collaborate with software, robotics, perception, and mech teams to design scalable, containerized pipelines, simulate sensor data, and validate models.

Qualifications

• Degree in CS/Robotics/Computer Vision or EE.
• 5+ years building platform infrastructure or autonomy software.
• Experience with containerization and orchestration.
• Proficient in Python and/or C++ for production software.
• Hands-on experience with robotics simulation tools.

Responsibilities

• Architect robotics and simulation infrastructure for self-driving labs.
• Develop and maintain containers and GPU on-demand infra.
• Create benchmarks and evals for robotics systems.
• Integrate simulation with ROS2 for software-in-the-loop testing.
• Collaborate with multi-disciplinary teams to meet design requirements.

Skills

Python

C++

CI/CD

Robotics simulation

Independent work

Education

Degree in Computer Science, Robotics, Computer Vision, Electrical Engineering

Tools

Isaac Sim

MuJoCo

Gazebo

Docker

Kubernetes

ROS/ROS2

Job description

Radical AI is replacing an R&D process that currently takes 10+ years and $100 million to produce a single discovery. Our self-driving lab platform combines AI with autonomous robotics to run experiments, analyze results, and iterate—continuously, without human bottlenecks. For industries like aerospace, automotive, defense, energy, manufacturing, semiconductors, and space, that means breakthroughs in weeks instead of years.

The Role

As a Software Engineer, Robotics Platform in the Robotics and Automation group at Radical AI, you will architect our robotics and simulation infrastructure that accelerates the development, validation, and deployment of intelligent robotic systems in our self-driving laboratories.

You will work closely with software, robotics, perception, mechatronics, mechanical engineering, and materials science to meet rigorous and sometimes dynamic design requirements at an unprecedented deployment speed.

What You'll Do

• Build the simulation infrastructure that facilitates our robotics team: robots, lab instruments, fixtures, sensors, and material-handling systems.
• Handle containerization for deployed and simulated systems
• Build and maintain infrastructure to support roboticists (e.g. on-demand GPU infrastructure)
• Build evals for robotics systems, including benchmarks for classical and learning-based methods
• Simulate RGB, depth, and other sensor data; generate synthetic datasets for object detection, segmentation, pose estimation, and scene understanding.
• Integrate simulation with ROS2 and for software-in-the-loop testing, regression testing, and deployment validation.
• Build reusable scenarios and automated tests for perception, task planning, robot behaviors, and failure recovery.
• Contribute to technical direction, architecture decisions, and best practices across the simulation and robotics platform.

What We're Looking For

Required

• Degree in Computer Science, Robotics, Computer Vision, Electrical Engineering, or equivalent experience
• 5+ years of experience developing platform infrastructure, robotics simulation, robotic perception, or autonomy software, including substantial hands-on simulation work
• Experience with containerization (e.g. Docker, Podman) and orchestration (e.g. Kubernetes), and CI/CD pipelines.
• Experience with a modern robotics simulation platform such as Isaac Sim, MuJoCo, or Gazebo.
• Proficiency in Python and/or C++ for production software development
• Ability to work independently in a hands-on, development-oriented environment.

Nice to Have

• Understanding of robot kinematics, motion planning, rigid-body physics, collision detection, and sensor modeling.
• Experience integrating machine learning frameworks (PyTorch, TensorFlow, Isaac Lab, or similar) into simulation pipelines for policy training, synthetic data generation, and autonomous behavior development.
• Experience with sim-to-real validation, synthetic data, or domain randomization.
• Experience with 2D/3D perception, camera geometry, calibration, and pose estimation.
• Experience with robotic control frameworks (e.g., ROS/ROS2 or equivalent custom systems)
• Experience deploying learned perception or multimodal models on physical robots.
• Experience with laboratory automation, materials science, or scientific instrumentation.