Research Engineer/ Scientist

Join us to shape the next frontier of AI-driven robotics! Dyna Robotics makes general-purpose robots powered by a proprietary embodied AI foundation model that generalizes and self-improves across varied environments with commercial-grade performance. Dyna's robots have been deployed at customers across multiple industries. Its frontier model has the top generalization and performance in the industry. Dyna Robotics was founded by repeat founders Lindon Gao and York Yang, who sold Caper AI for $350 million, and former DeepMind research scientist Jason Ma. The company has raised over $140M, backed by top investors, including CRV and First Round. We're positioned to redefine the landscape of robotic automation. Position Overview As a Research Engineer on the AI Research team, you will own the end-to-end loop of Embodied AI. You will leverage our massive, "in-the-wild" multimodal datasets to develop models that don’t just move - they generalize, self-improve, and redefine what is possible in unstructured human environments. What You’ll Do Advance the Frontier: Design and implement state-of-the-art robot learning algorithms (RL, Imitation Learning, Diffusion) for complex, high-DOF manipulation tasks. VLA & Video Generation: Architect and scale multi-modal foundation models (VLMs/VLAs) and leverage generative video architectures to enhance world-modeling and robot foresight. End-to-End Ownership: Own the full research-to-production pipeline: from task definition and data curation to large-scale training and real-time deployment on physical hardware. Physical-World Evaluation: Move beyond the benchmark. You will evaluate and iterate on models using our expanding robot fleet, ensuring commercial-grade performance in dynamic customer environments. Collaborative Leadership: Work at the intersection of AI, Hardware, and Teleop teams to enhance the "Intelligence-per-Watt" of our robotic systems. What You’ll Bring Research Excellence: A PhD (preferred) or Master’s in CS/Robotics with a significant publication record in top-tier conferences (RSS, CoRL, ICRA, NeurIPS, CVPR, or ICLR). 5+ Years of Mastery: Deep experience in AI and robotics research, specifically in deploying deep learning models onto physical robots (not just simulation). Generative AI Expertise: Hands-on experience with Vision-Language-Action (VLA) models, Video Generation, or large-scale transformer architectures. Technical Stack: Mastery of Python and PyTorch (or JAX). Familiarity with simulation stacks like MuJoCo, Isaac, or Drake. High-Quality Code: The ability to write maintainable, production-ready research code that scales across GPU clusters.