Education: Master's or Ph.D. in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, or a related field.
Experience: • 15+ years of experience in robotics, with specific expertise in humanoid, biped, quadruped, bionic, and industrial robotic systems. • 7+ years in a senior leadership role, managing multidisciplinary robotics and engineering teams. • Proven track record of designing and deploying autonomous robotic systems for industrial and manufacturing environments.
Technical Skills: • Advanced Robotics and Perception: Expertise in LiDAR, 3D mapping, SLAM, sensor fusion, and computer vision for robotic perception systems. • Mechanical Engineering and Motion Control: Extensive knowledge of robotic kinematics, actuation, and control for complex robotic systems, including humanoids and quadrupeds. • Edge AI and Real-Time Processing: Skilled in deploying AI models on edge devices with tools like TensorRT and CUDA, and optimizing systems for low-latency, high-performance applications. • Software Development: Proficiency in Python and C++ for ROS integration, simulation, and robotic control. • Robotics Frameworks: Extensive experience with ROS (Robot Operating System) and ROS2 for developing and integrating robotic systems. • AI and Machine Learning: Proficiency in TensorFlow, PyTorch, and scikit-learn for developing and implementing machine learning models in robotics applications. • Computer Vision Libraries: Strong knowledge of OpenCV, PCL (Point Cloud Library), and other relevant computer vision libraries for robotic perception. • Simulation Tools: Experience with Gazebo, Webots, or similar robotics simulation environments for testing and development. • Control Systems: Familiarity with control theory and implementation using libraries like control_toolbox or custom solutions. • Embedded Systems: Knowledge of programming for embedded systems, including real-time operating systems (RTOS) and microcontroller programming. • Version Control and Collaboration: Proficiency with Git and collaborative development platforms like GitHub or GitLab. • CI/CD for Robotics: Experience with continuous integration and deployment tools adapted for robotics development, such as Jenkins or GitLab CI. • Data Analysis and Visualization: Skill in using tools like Matplotlib, Plotly, or RViz for data analysis and visualization in robotics contexts. • Hardware Interfaces: Familiarity with communication protocols like I2C, SPI, CAN, and experience interfacing with various sensors and actuators.
Cloud Robotics: Experience with cloud platforms like AWS RoboMaker or Google Cloud Robotics for distributed computing and cloud-based robotics applications.
Reinforcement Learning: Proficiency in implementing RL algorithms for robotics, using frameworks like OpenAI Gym or RLlib.
CAD and 3D Modeling: Skill in using CAD software like SolidWorks or Fusion 360 for designing robotic components and systems.
Parallel Computing: Experience with CUDA or OpenCL for GPU acceleration in robotics applications.
Robotic Middleware: Familiarity with middleware solutions like YARP or OROCOS for real-time control and communication in complex robotic systems.
Preferred Qualifications:
Project and Resource Management: Experience with Agile methodologies, project management tools, and budget management for complex robotics projects. Demonstrated ability to manage multiple cross-functional teams effectively and ensure timely project completion.
MLOps and DevOps: Familiarity with MLOps practices for model deployment, monitoring, and retraining in production environments, as well as DevOps practices for CI/CD pipelines in robotics.
Manufacturing and Industrial Compliance: Knowledge of industry safety standards, regulatory compliance, and the unique challenges associated with deploying robotics in manufacturing and industrial settings.
Open-Source Contribution and Community Engagement: Proven experience contributing to open-source robotics, AI, or automation projects, with a commitment to leveraging and advancing community-driven innovation.
