Principal Robotics Engineer Bot Routing Jobs in California

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.

FieldAI is seeking a Principal Robotics Engineer to set technical direction across our autonomy software stack and to take ownership of our hardest, highest-leverage engineering problems. As a Principal-level individual contributor, you will architect production-grade systems spanning perception, localization, planning, and control; define the interfaces and quality standards that let dozens of engineers move fast without breaking the fleet; and translate cutting-edge research into reliable, field-ready capabilities running on legged and wheeled robots worldwide. This is a technical leadership role: you will multiply the output of the entire autonomy organization through architecture, mentorship, and cross-team influence rather than through people management.

• Autonomy Stack Leadership: Drive deep technical work across perception, localization and mapping, planning, and control. Identify the algorithmic and systems bottlenecks limiting reliability and performance, and personally lead the most difficult of them to resolution.
• Production Software Quality & Stable Interfaces: Define and enforce stable API contracts between autonomy components and the broader software platform. Raise the bar on production software quality through testing, code review, profiling, and architectural discipline.
• Cross-Team Technical Leadership & Mentorship: Align engineers across multiple teams on shared technical direction without formal authority. Mentor senior and staff engineers, review designs, and grow the technical depth of the organization.
• Research-to-Production Translation: Partner with research collaborators and internal scientists to mature promising methods—including learning-based traversability, foundation models, and learned planning—from prototypes into robust, deployed capabilities.
• Field Reliability & Incident Resolution: Lead root-cause analysis of complex, fleet-wide reliability and performance issues. Establish the observability, diagnostics, and engineering practices that keep robots operating reliably in real-world conditions.

• Master's or PhD in Robotics, Computer Science, Electrical Engineering, or a related field—or equivalent industry experience.
• 10+ years of experience building production robotics or autonomy software, with a track record of Principal- or Staff-level technical impact.
• Deep expertise in modern C++ and Python, with strong command of ROS/ROS2, Linux, and Git.
• Demonstrated experience architecting large-scale autonomy systems across two or more of: perception, SLAM/localization, planning, and control.
• Strong foundation in real-time systems, concurrency, and performance optimization.
• Proven ability to lead complex technical efforts across multiple teams and to influence direction without formal management authority.
• Excellent written and verbal communication; able to make sound architectural trade-offs and articulate them to engineers and stakeholders alike.

• PhD with a strong publication record in robotics, perception, or machine learning.
• Hands-on experience with both legged and wheeled robot platforms.
• Experience with learning-based methods for navigation, traversability, or planning, including vision foundation models or reinforcement learning.
• Experience with simulation environments such as Isaac Sim, Gazebo, or MuJoCo.
Track record of deploying and maintaining robot fleets in harsh or unstructured real-world environments.
• Familiarity with fleet observability and performance tooling (e.g., Prometheus, Grafana).