【2027研發替代役暨預聘】Robotics Infrastructure & DevOps Engineer_Delta Robotics Innovation Center (Taipei)

The Delta Robotics Innovation Center (DRIC) is established to support Delta Electronics’ long-term robotics development. Its primary purpose is to build and enhance Delta’s capabilities in robot design, manufacturing, and integration. Rather than focusing on delivering specific products, the center aims to cultivate core competencies that enable Delta groups to efficiently develop and commercialize robotics-based solutions.

Responsibilities:

• Design, implement, and optimize automated CI/CD, simulation, and automated testing pipelines tailored specifically for robotics software workflows.
• Develop robust and efficient firmware/software update mechanisms and configuration management systems for distributed edge devices.
• Architect and maintain high-availability edge-to-cloud communication infrastructure, optimized logging frameworks, and real-time metric collection systems.
• Optimize hardware resource utilization and maintain robust containerized environments (Docker/Kubernetes) ensuring predictable software execution on edge platforms.
• Design and develop a scalable, modular, and high-performance software framework for multi-robot systems.
• Establish MLOps/AIOps pipelines to automate model evaluation, optimize edge inference, and streamline continuous data collection from robots for retraining.
• Establish standardized modular tools to support robotics engineers in agile integration and streamline technology handovers for PoC.
• Transform prototype codebases into highly reliable, clean, and commercial-grade software products.

Motion Control Domain:

• Architect and develop next-generation robot motion control systems, covering low-level servo control, advanced manipulation control, and whole-body coordination.
• Develop high-performance real-time control algorithms for precise, compliant, and adaptive robot behaviors.
• Bridge high-level autonomy and low-level actuation by designing scalable interfaces between planning, control, and hardware execution layers.
• Explore and deploy model-based, optimization-based, and learning-based control approaches for advanced robotic applications.
• Enable intelligent manipulation through multi-modal feedback integration, including force, tactile, and vision-based sensing.