Senior Robotics Engineer, Mission Autonomy
Required skills
- Electrical Engineering
- Robotics
- AI-driven autonomy software
- real robots
- task and motion planning
- VLM/LLM-based planners
- state machines
- behavior trees
- low-level robotic manipulation
- runtime perception outputs
Nice to have
- Gazebo
- Isaac Sim
- UGV
- UAV
- mobile manipulator
- LLM/VLM-based long-horizon planning
Role summary
FieldAI is seeking a Senior Robotics Engineer for Mission Autonomy in Irvine, CA. This role involves designing and implementing advanced AI-driven robotic systems, focusing on perception-aware mission autonomy, VLM-based long-horizon reasoning, and multi-robot coordination. The ideal candidate will have a PhD or equivalent experience, advanced proficiency in Python, C++, ROS/ROS 2, Linux, Git, and Docker, with 5+ years of experience deploying AI autonomy software on real robots. Experience with simulation environments and multi-robot systems is a plus. This position offers the opportunity to work on cutting-edge robotics technology with a world-class team.
Who are We
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.
Learn more at https://fieldai.com.
About the Job
Field AI is seeking a rigorous and innovative Senior Robotic Autonomy Engineer for Mission Autonomy to play a vital role in the development of highly advanced robotic and AI systems by designing and implementing intelligent decision-making frameworks. Your contribution is essential to advancing our autonomous robotic platforms and delivering cutting-edge AI-driven solutions to customers. This is a unique career opportunity to join a rapidly growing company and contribute to the success of enterprise clients in a dynamic, fast-paced environment.What You’ll Get To Do
Perception-Aware Mission Autonomy: Couple runtime perception outputs (e.g. semantic 3D scene understanding) with world information, to create a unified semantic scene graph that enables perception-aware real-time mission planning and execution with spatial reasoning, feasibility validation, online task replanning, and natural language driven robotic autonomy.
VLM-Based Long-Horizon Reasoning: Design and implement a VLM-based mission controller that observes the robot's camera view and scene graph, reasons about mission progress, and selects actions from reusable primitives and tools, with step verification, failure detection and recovery, online replanning, and feedback handling for natural language driven long-horizon missions.
Multi-Robot Mission Autonomy: Support the development of a multi-robot mission autonomy framework for task allocation, execution monitoring, and coordination across heterogeneous robots, and expand the robotics testing framework through unit and integration tests to ensure system reliability, safety, and performance.
What You Have
PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
Advanced proficiency in Python programming, C++, ROS/ROS 2, Linux, Git, Docker
5+ years experience with AI-driven autonomy software deployed on real robots (e.g. task and motion planning, VLM/LLM-based planners, state machines, behavior trees) and low-level robotic manipulation skills
Ability to effectively and efficiently communicate with all teams, and to lead technical efforts across them
Strong problem-solving skills and proven ability to navigate complex software systems
Strong work ethic, highly self-motivated, and able to work independently while managing multiple priorities
The Extras That Set You Apart
Experience with simulation environments (e.g., Gazebo, Isaac Sim)
Experience with heterogeneous multi-robot systems (UGV, UAV, mobile manipulator)
Experience with LLM/VLM-based long-horizon planning and failure recovery in robotic systems
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