全职 Physical AI Heterogeneous System Design Engineer 工作, 薪水, China Telecom Singapore Innovation Research Institute 公司招聘中 - Ricebowl

Role Overview

We are looking for a pioneering Physical AI Heterogeneous System Design Engineer to redefine autonomous robotic manipulation through innovative hardware acceleration, physical AI software models, and real-time system control. You will design, develop, and deploy custom hardware accelerators using High-Level Synthesis (HLS) integrated with multimodal Vision-Language-Action (VLA) models and ROS 2 robotic arm control pipelines running on heterogeneous GPU + FPGA testbeds.

Key Responsibilities

• Develop, train, and optimize state-of-the-art Physical AI models using PyTorch/TensorFlow and ONNX workflows.
• Design, implement, and optimize custom hardware acceleration cores using High-Level Synthesis. Achieve strict timing closure and low-latency execution.
• Implement closed-loop robotic arm motion control using ROS / ROS 2 and physics-based simulation environments for trajectory data collection and model evaluation.
• Lead the end-to-end physical prototype demonstration — integrating camera vision feeds, force sensor inputs, VLA real-time inference results, and telemetry visualization dashboards.
• Map microsecond real-time motion control and sensor interfaces onto FPGA logic via PCIe and AXI4 bus interconnects.
• Translate high-level multimodal neural architectures into C/C++ HLS specifications and ROS 2 middleware APIs for robotic control.

Qualifications

• Ph.D. or Master’s in Electronic Engineering, Computer Engineering, Robotics, or a closely related discipline.
• Proficiency in PyTorch / TensorFlow, ONNX model deployment workflows, and ROS / ROS 2 for robotic motion control.
• Demonstrated experience in AI model optimization, multimodal AI frameworks (ViT, CNNs, LLMs, VLMs) and simulation tools (MuJoCo, robosuite, Isaac Sim).
• 3+ years of hands-on experience in High-Level Synthesis (HLS) design.
• Proven record in hardware timing closure, resource optimization, and interfacing systems with robotic actuators.
• Experience in Physical AI and VLA models and hands-on training/simulation for robotic arms.
• Strong programming skills in C, C++, and Python for embedded system drivers, hardware testbenches, and real-time execution.