Robotics AI Engineer – Field Foundation Models & Dynamics Foundation Models

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Field AI is transforming how robots interact with the real world. We build risk-aware, reliable, field-ready AI systems that address complex robotics challenges and unlock embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, with globally deployed solutions and continually improving models through real-field applications.

Are you driven to build next-generation AI-powered robotics? We seek a Robotics AI Engineer – Field Foundation Models & Dynamics Foundation Models to advance risk-aware, self-evolving robotic intelligence. You will design, develop, and implement cutting-edge AI-driven planning and control architectures so our robots operate in unstructured, high-stakes environments. This is your opportunity to redefine the future of embodied AI, collaborating with a world-class team that values bold innovation, hands-on execution, and AI-first engineering.

• Algorithm Development
• 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

• Software Integration and Testing
• 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

• Hands-On Robotics Deployment
• Collaborate with hardware teams to ensure seamless software-hardware integration
• Travel to customer sites to deploy, calibrate, and fine-tune robotic systems in diverse real-world conditions

• Cross-Team Collaboration
• 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

• Strong programming skills:
  Proficiency in Python and C++ for algorithm development and system integration
• Proficiency in ROS:
  Experience developing and integrating robotic software solutions
• Hands-on robotics experience:
  Practical experience with autonomous robotic systems, including field testing and deployment
• Understanding of planning and controls:
  Solid knowledge of path planning, control theory, and trajectory optimization
• Ability and willingness to travel:
  Travel to customer sites for deployments, testing, and troubleshooting (up to 30%)
• Excellent communication skills:
  Ability to convey complex technical concepts clearly to diverse audiences

• 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 (Bachelor’s, Master’s) in Robotics, Computer Science, Electrical Engineering, or a related field
• Understanding of safety standards and compliance in robotics

Our salary range is generous ($70,000 - $200,000 annual), with final pay based on background and experience. We consider location, knowledge, skills, and experience. Hybrid or remote options may be explored.

We’re solving one of the world’s most complex challenges: deploying robots in unstructured environments. Our Field Foundational Models set a new standard in perception, planning,…