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.
We’re building the software platform that enables FieldAI’s foundation models to run reliably and efficiently across a growing range of robots, hardware configurations, and real-world applications. As a founding member of the Robotics Platform team, you’ll help define the architecture, interfaces, and runtime systems that make our autonomy stack portable across embodiments while delivering the performance and reliability required for deployment in the physical world.
This role sits at the intersection of robotics, distributed systems, middleware, and performance engineering. You’ll work across the full system—from APIs and subsystem boundaries to communication middleware, runtime execution, simulation, and deployment on real hardware—solving the foundational problems that allow autonomy teams to move faster without coupling themselves to a particular robot or hardware stack.
A key part of the role is defining how robots describe themselves to the rest of the system. You’ll design the models and interfaces used to represent robot capabilities, current state, and intent so that dashboards, autonomous agents, fleet-management systems, and other services can reason consistently about what a robot can do, what it is doing, and what actions are valid. These abstractions need to remain useful as robots gain new sensors, behaviors, embodiments, and autonomy capabilities.
At the same time, you’ll tackle the systems challenges of making sophisticated robot intelligence practical at the edge: designing clean abstractions without sacrificing performance, moving large amounts of data efficiently through constrained systems, understanding latency and reliability end to end, and building infrastructure that behaves predictably outside the lab.
You’ll have significant influence over the technical direction of the platform and will work closely with autonomy, hardware, simulation, infrastructure, product, and deployment teams to turn cross-cutting requirements into durable systems and interfaces. The systems you build will directly determine how quickly FieldAI can bring its intelligence to new robots, integrate with fleet and operational tooling, and deploy new applications in the real world.