Physical AI Heterogeneous System Design Engineer

Job in Singapore, Singapore

Listing for: China Telecom Singapore Innovation Research Institute

Full Time position
Listed on 2026-10-15

Job specializations:

Software Development
Robotics, AI Engineer (Applied/Software), Embedded Systems/ Firmware/ IoT, Machine Learning/ ML Engineer

Salary/Wage Range or Industry Benchmark: 120000 - 180000 SGD Yearly SGD 120000.00 180000.00 YEAR

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/Tensor Flow 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 / Tensor Flow
, 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 (Mu Jo Co , 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 test benches, and real‑time execution.