What You’ll Get To Do
- Design, develop, and deploy AI algorithms for robotic perception, localization, mapping, planning, and control.
- Build and train machine learning models for robotic autonomy, including multimodal perception and decision-making.
- Develop scalable software systems for robotics using languages such as Python and C++.
- Integrate AI models with robotics hardware, sensors, and embedded systems.
- Improve robustness, reliability, and safety of robotic systems operating in real-world environments.
- Collaborate with robotics engineers, ML researchers, and systems engineers to deliver end-to-end autonomous solutions.
- Test and validate algorithms in simulation and real-world deployments.
- Analyze field data to improve model performance and system reliability.
What You Have
- Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Electrical Engineering, or related field.
- Strong programming skills in Python and/or C++.
- Experience with machine learning, deep learning, or AI for robotics.
- Knowledge of robotics frameworks such as ROS/ROS2.
- Experience with robot perception, SLAM, sensor fusion, or computer vision.
- Familiarity with simulation tools and robotics development environments.
- Strong problem-solving skills and ability to work in interdisciplinary teams.
The Extras That Set You Apart
- Experience with robot learning, reinforcement learning, or foundation models for robotics.
- Experience deploying AI models on edge systems or embedded platforms.
- Background in autonomous systems, navigation, or field robotics.
- Experience working with real robotic platforms and sensor systems (LiDAR, cameras, IMU, etc.).