Overview
Robotics AI Engineer
Full job description
Robotics AI Engineer Location: Singapore
Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.
About Field AI Field AI is at the forefront of robotic embodied AI, transforming industries like construction, security, mining, and manufacturing. Our autonomous robots operate globally, often in harsh environments, delivering critical insights to customers. Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, Field AI is advancing technology to make a meaningful impact.
Learn more at https://fieldai.com.
About the Job
As a Robotics AI Engineer, you will design and deploy AI algorithms that enable robots to perceive, reason, and act in unstructured environments. You will collaborate with cross-functional teams spanning robotics, machine learning, and systems engineering to bring cutting-edge autonomy solutions from research to real-world deployment.
Design, develop, and deploy AI algorithms for robotic perception, localization, mapping, planning, and control.
Build and train machine learning models for robotic autonomy, including multimodal perception and decision-making.
Develop scalable software systems for robotics using languages such as Python and C++.
Integrate AI models with robotics hardware, sensors, and embedded systems.
Improve robustness, reliability, and safety of robotic systems operating in real-world environments.
Collaborate with robotics engineers, ML researchers, and systems engineers to deliver end-to-end autonomous solutions.
Test and validate algorithms in simulation and real-world deployments.
Analyze field data to improve model performance and system reliability.
Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Electrical Engineering, or related field.
Strong programming skills in Python and/or C++.
Experience with machine learning, deep learning, or AI for robotics.
Knowledge of robotics frameworks such as ROS/ROS2.
Experience with robot perception, SLAM, sensor fusion, or computer vision.
Familiarity with simulation tools and robotics development environments.
Strong problem-solving skills and ability to work in interdisciplinary teams.
Experience with robot learning, reinforcement learning, or foundation models for robotics.
Experience deploying AI models on edge systems or embedded platforms.
Background in autonomous systems, navigation, or field robotics.
Experience working with real robotic platforms and sensor systems (LiDAR, cameras, IMU, etc.).
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