Postbaccalaureate Appointee - Robotics Software Developer, Rapid Prototyping Laboratory

Argonne National Laboratory • Lemont, IL

1d • $58,656 - $92,273

About The Position

The Rapid Prototyping Laboratory (RPL) in the Data Science and Learning division builds self-driving laboratories where robots, scientific instruments, and AI work together to run experiments with minimal human intervention. The Postbaccalaureate Appointee will develop robotics software for these laboratories and bring new robotic platforms into them.

The role integrates robotic hardware—including robotic arms, mobile manipulators, and humanoid platforms such as Dexmate—into autonomous laboratories. Work spans bringing an unfamiliar robot into the facility through to running experiments under laboratory orchestration software. The appointee will write and extend device modules and REST APIs in MADSci, an open-source laboratory orchestration framework, to make each platform controllable through a common laboratory interface.

The position also involves sensor integration and data collection for robot learning. The appointee will instrument robots with cameras, tactile and force sensors; collect demonstration data using teleoperation devices; and support training and evaluation of policies built on large robotics foundation models. They will help assess whether tasks are better suited to learned policies or conventional control.

Much of the work involves unfamiliar hardware and software, incomplete vendor documentation, and no established integration path. The appointee will collaborate with staff across robotics, software, and supported scientific domains. Contributions to MADSci will be released publicly.

Requirements

• Recently completed a bachelor's degree in computer science, robotics, electrical engineering, mechanical engineering, or a related field.
• Proficiency in Python, including experience writing code that others can read and maintain.
• Hands-on experience with robotic hardware, such as robotic arms, mobile robots, or humanoid platforms, including setup, calibration, and troubleshooting.
• Experience with a robot middleware or control framework such as ROS or ROS 2, or with a vendor SDK.
• Experience developing or consuming REST APIs.
• Familiarity with version control and collaborative software development using Git.
• Demonstrated ability to bring up unfamiliar hardware using vendor documentation and make progress when documentation is incomplete.
• Ability to communicate clearly with colleagues from robotics, software, and experimental science backgrounds.
• Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork.

Nice To Haves

• Experience integrating sensors with robotic systems, including cameras, tactile sensors, or force and torque sensing.
• Experience with teleoperation hardware and collecting demonstration data for robot learning.
• Familiarity with machine learning frameworks such as PyTorch and exposure to imitation learning, reinforcement learning, or robotics foundation models.
• Experience contributing to an open-source project.
• Exposure to laboratory automation, scientific instrumentation, or self-driving laboratories.
• Experience with containerized deployment using Docker.

Responsibilities

• Integrate robotic arms, mobile manipulators, humanoid platforms, and other robotic hardware into autonomous laboratories.
• Bring unfamiliar robotic platforms from initial setup through operation under laboratory orchestration software.
• Write and extend device modules and REST APIs in MADSci so robotic platforms can be controlled through a common interface.
• Integrate cameras, tactile sensors, and force sensors with robots.
• Collect robot demonstration data using teleoperation devices.
• Support training and evaluation of policies based on large robotics foundation models.
• Help determine which tasks are suitable for learned policies and which are better handled by conventional control.
• Collaborate with colleagues across robotics, software, and experimental science.
• Contribute to MADSci, with contributions released publicly.

Benefits

• Comprehensive benefits are part of the total rewards package.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level