Robotics Applied Scientist, Spatio-Temporal Scene Understanding & Memory

FieldAI; Irvine (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

FieldAI’s Irvine team develops embodied AI systems for real robots using real hardware and deployments. You will advance memory representations, world models, and physics-aware digital twins to enable robust, long-term autonomy in challenging environments.

The role requires a PhD in robotics or related field, hands-on experience with vision-language models, and strong Python/C++ skills to run methods on real robots with ROS 2.

Qualifications

• PhD in robotics, computer science, electrical engineering, aerospace or related field, with publications in top venues.
• Hands-on experience with vision-language or foundation models applied to spatial reasoning, memory, or long-horizon embodied QA.
• Depth in 3D representations: scene graphs, neural/ Gaussian-splat maps, or object-centric maps.

Responsibilities

• Investigate representation for robot's mission memory (persistent spatio-temporal).
• Build world models enabling reasoning and planning over memory and physics-aware twins.
• Combine learned and physically grounded models with geometry and dynamics as ground truth.
• Bridge perception-reasoning gap for long-term autonomy.

Skills

Python

ROS 2

C++

Vision-language

Spatial reasoning

Education

PhD in robotics or related field

Tools

ROS 2

C++

Python

Job description

FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.

What You Will Get To Do

• Investigate the appropriate representation for the robot's mission memory: a persistent spatio-temporal representation of what it saw, where, when, and how it changed, across missions and sites, so assets that move, disappear, or degrade are tracked rather than rediscovered.

• Build world models that let the robot reason and plan over that memory and recover physical parameters through interaction for physics-aware digital twins.

• Combine learned and physically grounded models, with geometry and dynamics as the ground truth.

• Bridge the perception-reasoning gap for long-term autonomy.

What You Have

• PhD in robotics, computer science, electrical engineering, aerospace engineering, mechanical engineering, or a related field, with publications at top venues such as RSS, CoRL, ICRA, IROS, T-FR, T-RO, CVPR, NeurIPS, or similar, on scene understanding, semantic SLAM, lifelong or spatio-temporal mapping, world models, or embodied reasoning.

• Hands-on experience with vision-language or foundation models applied to spatial reasoning, memory, or long-horizon embodied question answering.

• Depth in 3D representations: scene graphs, neural or Gaussian-splat maps, or object-centric maps, and the estimation underneath them.

• Strong Python; able to run your methods on real robots with C++ and ROS 2.

• Clear thinking about what a representation is for and how to evaluate it, and comfort with a fast-paced environment where research questions are set by what the next deployment needs.

What Will Set You Apart

• Change detection or long-term mapping results from real deployments.

• Real2Sim, system identification through interaction, or digital-twin work.

• Experience with behavior trees or task planning driven by language models.

• Industrial or field robotics exposure.

Our salary range is generous and we consider each individual’s background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.

Why Join FieldAI in Irvine?

In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics’ hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.

You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.

Be Part of the Next Robotics Revolution

We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.

Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like.

We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected status.