Researcher, Robot Intelligence
Samsung Research America
| Company | Samsung Research America |
| Category | Science & Research |
| Location | 665 Clyde Avenue |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 24 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Lab Summary: The Robot Intelligence Lab at Samsung Research America is a new facility dedicated to advancing the field of robotics through cutting-edge research and development. The lab’s mission is to develop advanced technologies to power intelligent robotic systems capable of manipulation, navigation, and complex reasoning for a variety of high-impact application areas. To achieve this mission, the lab collaborates closely with external entities such as universities, startups, and government labs, as well as with several Samsung Product and Advanced Research labs.
Position Summary: As the Robot Intelligence Lab grows, we will be hiring across multiple career levels including Senior, Staff and Senior Staff. The level at which a candidate is hired will reflect their experience, technical expertise and demonstrated impact.
Regardless of level we are looking to grow the team with Researchers who have solid technical skills and rich academic and/or industry experience in areas of robotics and embodied intelligence. Our ideal candidate explores novel technologies aimed towards generalizing robots to perform tasks in the real world. Samsung’s unique advantage in the consumer electronics market and growing focus on AI and robotics will provide you with exciting technical challenges and a rewarding career experience. By leveraging Samsung’s vast product ecosystem to deliver novel user experiences, your work will define Samsung’s future in robotics and significantly impact real-world users.
We are hiring candidates for multiple groups within the lab (Reasoning, Dexterity, Data Efficiency, and Robot Systems), and hence the responsibilities and required skills for each position will be group dependent.
Position Responsibilities:
Conduct state-of-the-art research to push boundaries of emerging fields of robotics, on topics such as task-and-motion planning (TAMP), world action models (WAMs), vision-language-action (VLA) models, vision language models (VLMs), open-world 3D perception, dexterous manipulation, real2sim2real, whole-body control, and multimodal (vision, tactile, audio, semantic) data fusion
Work with team to explore novel techniques, device interfaces, and model architectures to train robotic policies effectively with limited available data
Design autonomy architectures that interpret high-level task instructions and generate low-level task commands
Enable real-time video encoders with multi-view inputs for robust scene understanding, enable VLMs to reason about general task knowledge, including tool usage, object interactions, and task feasibility assessment, and enable Chain-of-Thought (CoT) task reasoning on VLM for complex, multi-step task execution
Develop efficient 3D scene graph representation and other 3D semantic/geometric models/solutions
Scale robot evaluation pipelines across robot fleets with a combination of simulation and real-world testing
Work within cross-functional, cross-divisional teams and assist in the design, analysis and performance evaluation from concept to completion
Generate patents and scientific research papers for top-tier publications
Required Skills:
PhD degree in EECS/Robotics or equivalent combination of education, training, and experience
2-14+ years’ experience in robotics
Strong research track record with publications in top-tier robotics, computer vision, or ML venues (e.g., ICRA, RSS, Science Robotics, CVPR, ICCV, ICML, NeurIPS)
Strong understanding of robotics fundamentals, including locomotion, manipulation, sensor inputs, pose tracking, 3D mapping, SLAM, ROS, and policy architectures particularly for semi-structured and unstructured environments
Experience with foundation models, vision-language-action (VLA) models, vision language models (VLMs), and agentic architectures
Solid understanding of computer vision techniques (e.g., object detection, segmentation, tracking) and real-time video tokenizer
You found the opening. Now track it.Tracker, radar and AI drafts in one place.erioun.com →