Job Purpose

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is expanding its research capacity in cutting-edge Robot Learning Laboratories. A vacancy of a Embodied-AI Engineer to join us, reporting directly to the Director of the Robot Learning Laboratory, is now required to advance the AI frontiers. This role emphasizes hands-on expertise in designing, developing, and deploying advanced robotic systems that bridge the gap between innovative research and practical real-world applications. As a key contributor to this state-of-the-art core facility, you will work directly with hardware and software systems to design, integrate, and optimize robotic platforms capable of operating in diverse and dynamic environments. Additionally, as a senior team member, you will lead efforts to enhance the laboratory’s development stack, ensuring scalability and efficiency as the team expands. This position is ideal for professionals passionate about leveraging robotics and AI research to drive transformative innovation in the field.

Key Responsibilities:

Technical Development:

• Plan, design, and implement scalable, resilient, and future-proofed technical solutions for robotic systems and AI applications.
• Identify, troubleshoot, and resolve application code-related issues, ensuring high reliability and performance across all technical implementations.
• Provide input on and adhere to code quality guidelines and standards, while advocating for best practices in software engineering within the team.
• Review and provide feedback on user documentation to ensure clarity, accuracy, and alignment with the lab’s standards and goals.

Research and Innovation:

• Design and develop novel AI-based learning and control algorithms for robotic systems, driving advancements in intelligent and autonomous robotic behavior.
• Integrate barrier certificates, AI models, and neural network-based dynamical systems to enhance the safety and reliability of robot navigation and manipulation in complex environments.
• Explore and implement compositional learning frameworks and advanced AI approaches to address high-dimensional and computationally challenging robotic tasks.

Collaborative Development:

• Work closely with a multidisciplinary team of researchers, engineers, and scientists to achieve the lab’s research and development objectives.
• Collaborate on the design, testing, and deployment of robotic platforms, ensuring alignment with the lab’s mission to advance state-of-the-art robotic and AI technologies.
• Support faculty, students, and researchers by providing technical guidance and contributing to joint projects and publications.

System Optimization:

• Lead efforts to enhance the lab’s development stack, focusing on scalability, efficiency, and integration of advanced AI technologies.
• Optimize robotic platforms for adaptability to diverse and dynamic environments, ensuring robustness in real-world applications.

Safety and Reliability:

• Develop and implement safe control mechanisms for robotic systems, ensuring adherence to safety standards and operational protocols.
• Evaluate and enhance the reliability of robotic systems through rigorous testing and validation processes.

Professional Development and Knowledge Sharing:

• Stay abreast of emerging trends in robotics, AI, and software engineering, integrating cutting-edge knowledge into the lab’s projects.
• Share expertise by mentoring junior engineers and researchers, fostering a culture of collaboration and continuous improvement within the team.

Strategic Contributions:

• Provide strategic input to the Director of the Robot Learning Laboratory, contributing to the planning and execution of the lab’s long-term vision and objectives.
• Engage in external collaborations, representing the lab in conferences, workshops, and industry partnerships to enhance the university’s reputation as a leader in robotics and AI research.

Other Duties:

• Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.

Academic Qualification

Bachelor’s or Master’s degree in Robotics, AI, Control Systems, Machine Learning, Computer Science, Electrical Engineering.

Professional Experience:

Essential:

• Mechanical Engineering, or a related field, with 5+ or 8+ years of industry experience.
• At least 2-3 years of hands-on experience with robotic system development and deployment.
• Strong expertise in robot learning, AI, control theory, and dynamical systems.
• Strong hands-on experience with robotic platforms, including assembly, programming, and maintenance. – Proficiency in robotics software frameworks (e.g., ROS, Gazebo) and programming languages (e.g., Python, C++, MATLAB).
• Practical knowledge of control systems, sensor integration, and real-time processing.
• Familiarity with deploying machine learning models, particularly reinforcement learning or control algorithms.
• Experience working with collaborative or humanoid robots in real-world environments.
• Background in sensor fusion and advanced perception systems for robotics.
• Understanding of NLP technologies for intuitive human-robot interaction.
• A proven track record of research excellence, as evidenced by publications in top-tier conferences and journals.

Preferred:

• Experience working in research-intensive environments or world-renowned research-based universities known for their AI expertise and innovation.
• Ability to work collaboratively in multidisciplinary teams, communicate complex technical concepts effectively, and adapt to evolving research requirements.