Robotics AI Engineer

Role Overview

Field AI is building dependable, risk-aware AI systems that help robots operate effectively in the physical world. The company focuses on embodied intelligence and real-world deployment, with solutions already running globally and improving through field data.

About Field AI

Field AI develops robotic embodied AI for industries such as construction, security, mining, and manufacturing. Its autonomous systems are used worldwide, including in demanding environments, to support tasks like construction monitoring, safety compliance, and predictive maintenance.

What the Role Involves

In this position, you will create and roll out AI methods that allow robots to perceive their surroundings, make decisions, and operate in unstructured settings. You will work closely with teams across robotics, machine learning, and systems engineering to move autonomy solutions from research into production.

Key Work Areas

• Develop and deploy AI methods for perception, localization, mapping, planning, and control in robots.
• Train machine learning models for robotic autonomy, including multimodal perception and decision-making.
• Write scalable robotics software using tools such as Python and C++.
• Connect AI models with robot hardware, sensors, and embedded systems.
• Strengthen reliability, safety, and resilience of robots used in real environments.
• Partner with robotics engineers, ML researchers, and systems engineers to deliver complete autonomy solutions.
• Run algorithm testing and validation in simulation and on actual robots.
• Review field data to raise model quality and improve system dependability.

Required Background

The role calls for a bachelor’s, master’s, or PhD in Computer Science, Robotics, Electrical Engineering, or a closely related discipline. Candidates should have strong programming ability in Python and/or C++, along with experience in machine learning, deep learning, or AI for robotics. Familiarity with ROS or ROS2, plus hands-on exposure to perception, SLAM, sensor fusion, or computer vision, is expected. You should also be comfortable with simulation tools and robotics development environments, and able to solve problems in interdisciplinary teams.

Preferred Experience

Additional value will be given to candidates with experience in robot learning, reinforcement learning, or foundation models for robotics. Exposure to deploying AI on edge devices or embedded platforms is also beneficial, as is a background in autonomous systems, navigation, or field robotics. Experience working with real robots and sensors such as LiDAR, cameras, and IMUs is a strong advantage.

Work Setup

This is a fully onsite role based in Singapore. Field AI values in-person collaboration for complex work and offers flexible hours to support work-life balance.

Culture and Inclusion

Field AI states that it welcomes applicants from all backgrounds and is committed to a diverse, inclusive workplace. Hiring and employment decisions are based on merit, qualifications, and performance, without discrimination on protected characteristics.

AI in Hiring

The company may use AI tools during recruitment to help review applications, analyze resumes, and check responses for inconsistencies or verification signals. These tools support the recruitment team, while final hiring decisions remain with humans. Candidates may contact the company for more details about how data is processed.

Why Join

You will work on one of the toughest problems in robotics: enabling robots to operate in unknown, unstructured environments. The team emphasizes explainable and safe deployment, and brings together experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX.

The company also highlights a strong track record, including field deployments and DARPA challenge wins, and describes the team as creative, resilient, ambitious, and close-knit.