Principal Physical AI Engineer (ROS Architect)

St Engineering; Singapore; On-site; SGD 180,000 - 260,000; Full time

Benefits offered by this job

State-of-the-art robotics

Professional growth

On-site work in Singapore

Job summary

St Engineering in Singapore is seeking a ROS Architect to define, configure and optimize the software backbone of next‑gen Physical AI systems. You will push beyond standard implementation, tune latency, security, and DDS configurations for reliable autonomous operation.

The role demands deep ROS1/ROS2 expertise, strong C/C++/Rust skills, and a track record of low‑level systems work on Linux, with Docker experience and collaboration across hardware, software, and QA teams.

Qualifications

• Masters or PhD in CS/ML/AI/Robotics required.
• 10–15 years (Masters) or 3–5 years (PhD) robotics experience.
• Strong OS internals, memory management, multi-threading and concurrency.
• Expert knowledge of Ubuntu Linux, Bash, networking.
• Deep ROS1/ROS2 knowledge with DDS/Middleware.
• Proficiency in C, C++, Rust; Assembly for tuning.
• Experience with robotics algorithms (SLAM, Kalman, planning).

Responsibilities

• Design robust ROS architectures and workspace structures.
• Configure QoS, security, and executor; modify client libraries.
• Develop, maintain and containerize complex ROS launch configurations.
• Design, code, test and debug nodes/services/actions in C++ or Python.
• Optimize Linux kernel for low-latency robotics performance.
• Diagnose and fix low-level system failures and memory issues.
• Develop and integrate middleware (DDS, MQTT) for real‑time data exchange.
• Develop and optimize device drivers for sensors and actuators on Linux/ROS.
• Collaborate with hardware, software and QA teams; produce system docs.

Skills

ROS

C

C++

Rust

Assembly

Linux

Concurrency

Memory management

Education

Masters/PhD in Computer Science, Machine Learning, AI, Robotics, or related field

Tools

CUDA

TensorFlow

PyTorch

DDS

MQTT

Docker

Job description

Are you a Robot Operating System ( R OS) expert who thrives on making robots run more efficiently, reliably and securely? We are seeking a highly skilled ROS Architect to define, configure, and optimize the software backbone of our next-generation Physical AI Brain. In this role, you will move beyond standard implementation to advanced customisation; from tuning system performance, minimizing latency, and ensuring robust and secured DDS (Data Distribution Service) configuration for real-world autonomy.

Key Responsibilities:

• ROS Architecture Design: Define and implement robust ROSarchitectures, including workspace structure, package management, and node communication paradigms.
• ROS Configuration and Client Library Modification: Configure ROS QoS policies and security features, runtime management (Executor), and modify/add client libraries.
• ROS Launch & Deployment: Develop, maintain, and containerize (Docker) complex launch configurations and parameter management systems.
• ROS Development & Integration: Design, code, test, and debug software nodes, services, and actions in C++ or Python to control Physical AI systems.

• Edge Compute OS Optimization: Customizing Linux kernel performance, scheduling, and resource allocation to ensure low-latency performance for robotics applications and other safety-critical tasks.
• System Diagnostics & Troubleshooting: Identifying and resolving low-level system failures, debugging race conditions, and handling memory management to improve stability.
• Middleware Development & Integration: Designing and managing the communication framework (e.g., DDS, MQTT) that allows nodes, sensors, and actuators to exchange data in real-time.
• Driver Development: Writing and optimizing device drivers for sensors (Lidar, cameras, IMUs) and actuators (motors, servo controllers) to work with Linux and ROS.
• Collaboration and Documentation: Working closely with hardware engineers, application teams, and QA testers, and creating technical documentation for system architecture.

Minimum Requirements:

• Education: Masters/PhD in Computer Science, Machine Learning, AI, Robotics, or related field.
• Experience: Masters (10 – 15 years)/ PhD (3-5 years)of experience building robotics/Physical AI systems.
• Operating Systems Internals: Strong understanding of operating system concepts, including process management, multi-threading, concurrency, memory management (paging/virtual memory), and interrupt handling.
• Linux Environment: Expert knowledge of Ubuntu Linux, terminal usage, shell scripting (Bash), and networking (TCP/IP).
• ROS Expertise: Deep knowledge of ROS1 & ROS 2, especially ROS 2 and its middleware components (DDS, FastDDS/CycloneDDS).
• Robot Behaviour Orchestration: Experience with Behavior Trees and other robot behavior orchestration frameworks.
• Programming Languages: Deep proficiency in CandC++is essential for kernel-level development, withRustincreasingly required for modern systems, andAssemblyfor debugging and performance tuning.

Good to Have:

• GPU Acceleration: Experience with CUDAprogramming for GPU acceleration.
• Edge AI Deployment: Optimizing models (TensorFlow/PyTorch) to run on low-power OS environments.
• Robotics Core Algorithms: Understanding of Kinematics, Dynamics, SLAM (Simultaneous Localization and Mapping), Kalman Filters, and Path Planning.
• GenAI for Robotics: Experience with implementing LLM based Semantic Reasoning and Task Decomposition for decision making, and/or VLM based Perception/Mapping for world state estimation.

Soft Skills:

• Problem-Solving: Methodical approach to diagnosing and resolving complex, low-level issues.
• Attention to Detail: Meticulous approach, as small errors in OS code can have significant consequences.
• Communication: Ability to explain complex technical concepts clearly to cross-functional teams.

What We Offer:

• Opportunity to work on state-of-the-art embodied AI models powering real robots.
• Combination of research and deployment - not just writing models, but seeing them act in the physical world.
• High-impact work on cutting-edge robotic autonomy and swarm behaviours.
• Exposure to both AI and hardware-level execution environments.