Robotics Software Engineer Vision-Language-Action Models
Confirmed on the employer's own hiring board on Sep 23, 2026. First seen by Alion on Jun 30, 2026.
Robotics Software Engineer Vision-Language-Action Models
Location
Trondheim, Norway or San Jose, California, US.
Role
As a Robotics Software Engineer specializing in robot learning and manipulation, you will drive the design, training, validation, and deployment of contact-rich manipulation skills on real robots. Your focus will be on solving dexterous, contact-rich manipulation tasks. You will develop and integrate sensor-based control strategies and Vision-Language-Action (VLA) policies, managing the full model lifecycle, from architecture and large-scale data collection through training, validation, and reliable deployment on industrial and collaborative robots.
This is a hands-on engineering role. You will spend significant time in the lab, running trials on hardware, curating high-quality datasets, and getting models to work on real robotic systems.
How you'll move the mission forward
Develop, train, and deploy multimodal VLA and learned manipulation policies that solve contact-rich tasks, integrating sensor-based control strategies that combine vision, force-torque, and tactile feedback.
Run the manipulation model lifecycle, conducting regular trials on real hardware to evaluate algorithmic changes and curate high-quality training datasets.
Architect and build modular components for imitation and reinforcement learning, continuously improving the robustness of contact-rich tasks.
Build pipelines for continual learning, enabling policies to keep improving from new demonstrations and real-world deployment data over time.
Stress-test and optimize the real-time execution framework for learned policies running on the robot.
Skills you will need to be successful
A Master’s or PhD degree in robotics, computer science, machine learning, or a related field, or equivalent professional experience in robot learning and manipulation (e.g. visuomotor policy learning, imitation learning, applied reinforcement learning,, Vision-Language-Action models).
Professional experience in Python and C++, with a proven track record of shipping production-quality code.
Deep expertise with a modern ML framework (PyTorch preferred; JAX or TensorFlow also welcome).
Direct experience testing and iterating on physical robots integrated with vision, force-torque, and tactile sensors.
Experience with robotic simulation environments (MuJoCo, Isaac Sim, Drake, or similar).
You thrive in the lab, spending significant time running hardware experiments and troubleshooting real-world edge cases.
Business fluency in English.
Skills that will differentiate your candidacy
Experience manipulating and analyzing complex, large-scale, high-dimensional multimodal data from varying sources, with proficiency training models at scale on cloud-based workflows.
Experience with edge deployment and model optimization for real-time control: low-latency inference, quantization, distillation, and pruning to meet tight control-loop rates on resource-constrained, on-robot hardware and accelerators.
Contributions to robot learning through publications or open-source projects.
Familiarity with ROS 2 and hands-on experience using industrial and collaborative robots from vendors such as Universal Robots, ABB, Fanuc, and KUKA.
Experience with multibody dynamics simulators such as Adams.