**Title: Applied AI Robotics Engineer
Location: Remote
Duration: 12+ months
Required Qualifications**
PhD in a relevant STEM field, or Master’s with equivalent industry experience in robotics, robot learning, or embodied AI.
Proven experience building and deploying machine learning models on robotic systems—including training, evaluation, and real-world execution or simulation.
Deep understanding of modern AI architectures (e.g., Transformers, diffusion models, VLM/VLAs, CNNs) with strong experience training models at scale.
Strong PyTorch implementation skills, including authoring custom modules, batching, debugging, and performance optimization.
Practical experience with ROS/ROS2 and integrating learned policies into manipulation or motion control workflows.
Demonstrated impact via robot learning publications, open-source contributions, or production robotics deployments.
Preferred Qualifications
Experience developing robot learning systems for dexterous manipulation, multi-step task execution, or autonomous behaviors.
Expertise in robotics perception, including 3D understanding, force sensing, tactile feedback, multimodal fusion, or affordance modeling.
Familiarity with Isaac Sim, Mujoco, Gazebo, PyBullet, or custom simulators, and demonstrated ability to transfer policies to hardware.
Experience adapting foundation models (VLM/VLAs, diffusion, instruction-following agents) for embodied control tasks.
Track record of production-ready robotics systems, reproducible research artifacts, or deployments in physical environments.
EoE