Physical AI Heterogeneous Systems Design Engineer
Salary: $7,000 – $9,000 per month
Physical AI Heterogeneous Systems Design Engineer
About the role
We are looking for a pioneering Physical AI Heterogeneous Systems Design Engineer to redefine autonomous robotic manipulation through hardware acceleration, physical AI software models, and real-time system control. This role designs, develops, and deploys 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 optimise state-of-the-art Physical AI models using PyTorch/TensorFlow and ONNX workflows.
Design, implement, and optimise custom hardware acceleration cores using High-Level Synthesis, achieving 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 end-to-end physical prototype demonstrations — integrating camera vision feeds, force-sensor inputs, VLA real-time inference results, and telemetry visualisation 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.
About you
PhD 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 optimisation, 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 optimisation, and interfacing systems with robotic actuators.
Experience with 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.
HOW TO APPLY:
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We regret to inform that only shortlisted candidates will be notified. All applications will be treated with the strictest confidence.
Allison Ng Kim Lian
Registration no. R1986496EA
License: 12C6253
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