1.5 Robotics AI Engineer – Field Foundation… at FieldAI · Irvine

Summary: FieldAI is transforming how robots interact with the real world by building advanced AI systems for robotics. The Robotics AI Engineer will design and implement AI-driven planning and control architectures to enhance robotic performance in complex environments. Responsibilities: - Design and implement next-generation AI-powered Field Foundation Models (FFMs) and Dynamics Foundation Models (DFMs) - Pioneer risk-aware, uncertainty-driven decision-making architectures that enable autonomous robots to navigate unstructured, high-stakes environments - Reimagine planning algorithms, trajectory optimization, and task scheduling as a fusion of probabilistic reasoning, geometric intelligence, and adaptive AI, ensuring precise and reliable robot motion in dynamic environments - Work extensively with ROS (Robot Operating System) to develop, test, and integrate next-gen autonomous intelligence modules - Design, implement, and test real-world and simulation-learning loops, where self-evolving models refine planning, control, and perception through real-world interaction - Conduct field tests to validate performance and optimize system behavior - Collaborate with hardware teams to ensure seamless software-hardware integration - Travel to customer sites to deploy, calibrate, and fine-tune robotic systems in diverse and challenging real-world conditions - Work closely with other engineering teams to align development efforts and achieve cohesive system performance - Communicate effectively with non-technical stakeholders to explain robotic capabilities and project progress Required Qualifications: - Strong programming skills: Proficiency in Python and C++ for algorithm development and system integration - Proficiency in ROS (Robot Operating System): Experience developing and integrating robotic software solutions - Hands-On Robotics Experience: Practical experience working with autonomous robotic systems, including testing and deployment in the field - Understanding of Planning and Controls: Solid knowledge of path planning, control theory, and trajectory optimization - Ability and availability to travel: Ability and eagerness to travel to customer sites for deployments, testing, and troubleshooting (up to 30% travel) - Excellent Communication Skills: Ability to convey complex technical concepts clearly to diverse audiences Preferred Qualifications: - Experience with GPU programming (CUDA C++, PyTorch) a significant plus - Experience with real-time systems or robotics middleware - Familiarity with sensor integration and perception algorithms - Knowledge of machine learning techniques applied to robotics - Exposure to industrial robotics applications in sectors like construction, mining, or manufacturing - Experience working in harsh or outdoor environments - Experience working with humanoid or legged robots - Advanced degree (Bachelors, Master's) in Robotics, Computer Science, Electrical Engineering, or a related field - Understanding of safety standards and compliance in robotics Required Skills: Python, C++, ROS, Robotics Experience Important Skills: Controls, Planning Nice-to-Have Skills: GPU Programming, Real-time Systems, Sensor Integration, Machine Learning