Job Description
As a Research Scientist in Embodied AI for Robotics, you will pioneer advanced research that sits at the intersection of machine learning, simulation, and physical robotic systems. You will lead efforts in developing novel AI-driven robotic capabilities, including multimodal perception, dexterous manipulation, reinforcement learning, motion generation, and simulation-to-real transfer.
You will work closely with engineers and scientists to translate cutting-edge research into production-ready robotic intelligence.
Roles and Responsibilities:
- Pioneer and lead research or translation of research into industrial robotics applications, focusing on AI for robotics.
- Develop novel algorithms and models for manipulation, navigation, and adaptive autonomy in complex manufacturing environments.
- Build and refine high-fidelity simulation environments using tools such as Isaac Sim, Gazebo, or custom simulators.
- Apply machine learning and deep learning techniques to improve robot control, adaptability, and decision-making in real-world scenarios.
- Architect and collaborate with engineers to develop proof-of-concept software solutions and demonstrators based on research outcomes using languages like C++ and Python and libraries such as ROS.
- Support integration of perception tools (e.g., vision, force/torque) to enable better object handling and environmental interaction.
- Drive application-oriented robotic research towards industrial automation.
- Publish research findings in top-tier robotics/AI venues and develop technical documentation.
Job Requirements:
- PhD degree in Robotics Engineering, Software Engineering, Computer Engineering, Electrical Engineering or Computer Science.
- Min. years of experience: 3-5 years.
Essential Skills & Experience:
- Strong proficiency in C++ and Python.
- Experience with ROS and its ecosystem (ROS/ROS2).
- Expertise in AI/ML model development, including reinforcement learning or imitation learning.
- Basic familiarity with deep learning frameworks such as PyTorch or TensorFlow is advantageous.
- Experience with Isaac Sim, Gazebo, Webots, or equivalent robotics simulators.
- Familiarity with Git, collaborative code workflows, and the software development lifecycle.
- Demonstrated ability to pioneer research or translate research findings into practical software prototypes or applications.
- Understanding of the Software Development Lifecycle (SDLC) and proficiency with Git version control.
Desired Skills & Experience:
- Experience with CI/CD and containerization (e.g., Docker, Kubernetes).
- Experience with software systems integration, architecture, communication protocols, and networked systems.
- Experience managing research projects or leading technical initiatives.
- Experience working with industry partners and presenting technical work.
- Prior experience in using/operating humanoids or working in semicon equipment sector is an added advantage.
- Candidates should be prepared to present their approach to pioneering research or translating research into industrial robotics applications, focusing on AI for robotics, advanced multi-robot coordination, or path planning, or propose an alternative research translation initiative.
