Careers at Field Ai

Location: Irvine, CA 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(1) 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. About Field AI Field AI is at the forefront of robotic embodied AI, transforming industries like construction, security, mining, and manufacturing. Our autonomous robots operate globally, often in harsh environments, delivering critical insights to customers. Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, Field AI is advancing technology to make a meaningful impact. Learn more at https://fieldai.com. About the Data Platform Team Every robot we deploy generates a continuous stream of telemetry, sensor logs, and operational data from environments around the world. The Data Platform team builds the systems that capture every autonomy intervention, anomaly, and operational signal from globally deployed robots, classify them, and turn them into the ranked problem list that drives our engineering roadmap. About the Job As a Data Platform Engineer, Infrastructure, you will build and operate the cloud foundation the entire data platform runs on — the systems every robot log, dashboard, and model-training run depends on. You will collaborate with pipeline and analytics engineers, as well as edge and robotics teams, to keep the platform reliable, secure, and cost-efficient as our fleet grows.

FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use.

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’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. Hardware Team: The Hardware Team at Field AI develops perception and compute payloads that power autonomous robotics systems in complex real world environments. Our work spans the full hardware stack designing and integrating sensing systems (LiDAR, camera, TOF, IMU, GPS), embedded compute (CPUs, GPUs, microcontrollers, Linux, ROS), electrical systems (power distribution, communication), and mechanical components (structures, thermal regulation, ingress protection). The team focuses on both development (research, design, prototyping, testing) and operations (production, testing, QA, debugging). We’re a small, fast-moving team, and we care deeply about improving: 1) core capabilities, 2) system reliability, 3) system scalability. As a growing team we are also building operational systems and procedures from the ground up. Electrical Systems Role: As an Electrical Engineer on the Humanoids Team at Field AI, you will work on advanced perception, compute, and manipulation systems for humanoid robotics. You will also work closely with advanced ML teams to ensure our robots can complete increasingly complex tasks. Your work will span across power systems, high speed communication, and PCB design with the goal of ensuring our systems are electrically robust, safe, and scalable. Responsibilities may span the full lifecycle from electrical CAD through production to field support. You will collaborate closely with the mechanical, sensor, and compute teams to build tightly integrated solutions ready for deployment in challenging field environments. While your focus will be on electrical systems you will likely contribute across all hardware domains. What You Will Get To Do 1. Electrical System Design Power Architecture: Design regulated power systems including voltage rails, DC/DC converters, switches, fuses, and grounding schemes. Wire Harness Design: Design and document robust wire harnesses for power and data lines, including shielding, strain relief, and standard connectors. PCB Design: Create PCBs for power distribution, protocol bridging, and embedded control. Networking & Communication: Architect wired and wireless communication systems (Ethernet, USB, CAN, I2C, WiFi, 5G). Budgets & Tolerances: Maintain system-level power and bandwidth budgets. Ensure electrical tolerance to noise, EMI, and vibration. 2. Electrical System Implementation CAD & Schematics: Create PCB schematics, harness diagrams, pinouts, and complete PCB BOMs using tools like KiCAD or Altium. Calculations: Conduct electrical calculations including current draw, peak power, signal integrity, and fault analysis. Design for Field Conditions: Engineer for EMI/EMC robustness, thermal resilience, and fault isolation under field operating conditions. Testing: Conduct power validation (noise, load, transients), communication tests (bandwidth, latency), and EMI evaluation. Integration: Collaborate with sensor, compute, and mechanical teams to ensure end-to-end system compatibility and robustness. Documentation & Budgets: Maintain PCB schematics and systems level wiring diagrams. Manage system-level power and data bandwidth budgets. 3. Electrical System Production & Servicing Build: Work with vendors and contract manufacturers to procure PCBs and harnesses. Develop QA checks for incoming units. Debug: Investigate system faults using logs, oscilloscopes, analyzers, and power monitors. Support: Provide hands-on support during integration, deployment, and servicing in the field. What You Have Education: B.S., M.S., or Ph.D. in Electrical Engineering, Computer Engineering, Robotics, or a related field. Experience Level: We are recruiting across a wide range of experience levels from entry level engineers to senior and staff engineers. Power Systems: Experience designing and testing low-voltage regulated power systems. Harnessing: Hands-on design and integration of custom wire harnesses for robotics or automotive-style systems. PCB Design: Proficiency in PCB schematic and layout using KiCAD, Altium, or equivalent tools. Communication Protocols: Familiarity with USB, Ethernet, CAN, I2C, GMSL, and wireless technologies. Testing & Debugging: Skills using electrical test tools including oscilloscopes, power analyzers, and EMI/EMC setups. Documentation: Ability to produce detailed electrical documentation for design, manufacturing, and servicing. Systems Thinking: Experience working across mechanical, compute, and autonomy teams to deliver robust integrated systems. Cross Functional Robotic Skills: Ability to contribute electrical, sensing, and embedded computing work to deliver robust integrated systems. What Will Set You Apart Scaling: Experience taking systems from prototype to large scale production. Field Environments: Experience developing systems for harsh field environments. Deployed Robotics: Experience working on robotics deployed in real world settings such as autonomous vehicles, drones, or ruggedized robots. Systems Level Robotics: Fluency across electrical, mechanical, and software systems. Reliability Engineering: Background in fault protection, EMI/EMC compliance, and safety-critical design.

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. Hardware Team: The Hardware Team at Field AI develops perception and compute payloads that power autonomous robotics systems in complex real world environments. Our work spans the full hardware stack designing and integrating sensing systems (LiDAR, camera, TOF, IMU, GPS), embedded compute (CPUs, GPUs, microcontrollers, Linux, ROS), electrical systems (power distribution, communication), and mechanical components (structures, thermal regulation, ingress protection). The team focuses on both development (research, design, prototyping, testing) and operations (production, testing, QA, debugging). We’re a small, fast-moving team, and we care deeply about improving: 1) core capabilities, 2) system reliability, 3) system scalability. As a growing team we are also building operational systems and procedures from the ground up. Electrical Systems Role: As an Electrical Engineer on the Hardware Team at Field AI, you will contribute to the design and implementation of electrical systems that enable power and communications across the sense and compute packages. Your work will span across power systems, wire harnesses, PCB design, and communications networks with the goal of ensuring our systems are electrically robust, safe, and scalable. Responsibilities may span the full lifecycle from electrical CAD through production to field support. You will collaborate closely with the mechanical, sensor, and compute teams to build tightly integrated solutions ready for deployment in challenging field environments. Additionally, while your focus will be on electrical systems you will likely contribute across all hardware domains. What You Will Get To Do 1. Electrical System Design Power Architecture: Design regulated power systems including voltage rails, DC/DC converters, switches, fuses, and grounding schemes. Wire Harness Design: Design and document robust wire harnesses for power and data lines, including shielding, strain relief, and standard connectors. PCB Design: Create PCBs for power distribution, protocol bridging, and embedded control. Networking & Communication: Architect wired and wireless communication systems (Ethernet, USB, CAN, I2C, WiFi, 5G). Budgets & Tolerances: Maintain system-level power and bandwidth budgets. Ensure electrical tolerance to noise, EMI, and vibration. 2. Electrical System Implementation CAD & Schematics: Create PCB schematics, harness diagrams, pinouts, and complete PCB BOMs using tools like KiCAD or Altium. Calculations: Conduct electrical calculations including current draw, peak power, signal integrity, and fault analysis. Design for Field Conditions: Engineer for EMI/EMC robustness, thermal resilience, and fault isolation under field operating conditions. Testing: Conduct power validation (noise, load, transients), communication tests (bandwidth, latency), and EMI evaluation. Integration: Collaborate with sensor, compute, and mechanical teams to ensure end-to-end system compatibility and robustness. Documentation & Budgets: Maintain PCB schematics and systems level wiring diagrams. Manage system-level power and data bandwidth budgets. 3. Electrical System Production & Servicing Build: Work with vendors and contract manufacturers to procure PCBs and harnesses. Develop QA checks for incoming units. Debug: Investigate system faults using logs, oscilloscopes, analyzers, and power monitors. Support: Provide hands-on support during integration, deployment, and servicing in the field. What You Have Education: B.S., M.S., or Ph.D. in Electrical Engineering, Computer Engineering, Robotics, or a related field. Experience Level: We are recruiting across a wide range of experience levels from entry level engineers to senior and staff engineers. Power Systems: Experience designing and testing low-voltage regulated power systems. Harnessing: Hands-on design and integration of custom wire harnesses for robotics or automotive-style systems. PCB Design: Proficiency in PCB schematic and layout using KiCAD, Altium, or equivalent tools. Communication Protocols: Familiarity with USB, Ethernet, CAN, I2C, GMSL, and wireless technologies. Testing & Debugging: Skills using electrical test tools including oscilloscopes, power analyzers, and EMI/EMC setups. Documentation: Ability to produce detailed electrical documentation for design, manufacturing, and servicing. Systems Thinking: Experience working across mechanical, compute, and autonomy teams to deliver robust integrated systems. Cross Functional Robotic Skills: Ability to contribute electrical, sensing, and embedded computing work to deliver robust integrated systems. What Will Set You Apart

Who are We? Field AIis 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 At FieldAI, we build autonomous robotic systems that operate in demanding, real-world environments where tight integration between hardware and software is critical. We’re looking for an Embedded Systems Engineer to support design, implementation, integration, and , deployment of wheeled robotic platforms across both federal and commercial programs Embedded Systems Role: As an Embedded Systems Engineer on the Federal Team at Field AI, you will contribute to the architecture, configuration, and validation of the compute systems that serve as the backbone for our robotic platforms. Your work will span low-level firmware, Linux-based configuration, and system performance analysis across ARM and x86 SBC platforms. From firmware on microcontrollers to ROS data streams on SBCs, you’ll ensure the entire compute stack is optimized, reliable, and robust under field conditions. You will collaborate closely with the sensor, electrical, and autonomy teams to build tightly integrated solutions ready for deployment in challenging field environments. Additionally, while your focus will be on computing systems you will likely contribute across all hardware domains. What You Will Get To Do 1. Compute System Design Compute Architecture: Architect and configure embedded compute platforms (ARM/x86, SBCs) for robotic applications including evaluation, testing and selection. Firmware & Software: Set up and customize Linux environments (Ubuntu, Yocto, JetPack), middleware (ROS), and I/O interfaces. Systems Integration: Integrate compute with sensing and robotic systems. Analyze thermal, power, and bandwidth constraints to meet deployment and runtime requirements. 2. Compute System Implementation Communications: Bring up sensors and peripherals using a range of protocols (USB, Ethernet, GMSL, I²C, SPI, CAN). Data Pipelines: Build and maintain drivers, ROS nodes, and data acquisition pipelines for new hardware components. Systems Configuration: Create configuration files, launch scripts, and firmware update workflows. Testing: Conduct system-level tests such as thermal profiling, latency measurement, and power draw analysis. Documentation & Budgets: Maintain flashing procedures, I/O maps, and debug kits. Manage compute and I/O budgets. 3. Compute System Production & Servicing Build: Work with vendors to procure compute hardware. Develop QA checks for incoming units. Support payload integration and scaling. Debug: Support root-cause analysis for boot, connectivity, and throughput issues. Diagnostics Monitoring: Implement watchdogs, health checks, and other evaluation tools. Monitor compute system performance across CPU, GPU, memory, I/O, and networking. What You Have Education: B.S., M.S., or Ph.D. in Computer Engineering, Robotics, Electrical Engineering, or a related field. Experience Level: We are recruiting across a wide range of experience levels from entry level engineers to senior and staff engineers. Embedded Systems: Experience with embedded platforms (Jetson, Raspberry Pi, x86 NUCs, custom SBCs). Linux: Proficiency with Linux system configuration, scripting, and headless deployment tools. Firmware: Strong skills in firmware development for microcontrollers, including bare-metal and RTOS environments. Programming: Proficient in C++ and Python for embedded and application-level development. Communication Protocols: Experience with USB, Ethernet, I²C, SPI, CAN, GMSL, and similar interfaces. ROS Ecosystem: Familiarity with ROS, device drivers, TF, and data streaming/publishing. Debugging: Comfort with hardware/software debugging tools (oscilloscopes, logs, power monitors, analyzers). Systems Thinking: Ability to diagnose and optimize across compute, thermal, timing, and I/O layers. What Will Set You Apart Scaling: Experience taking systems from prototype to large scale production. Field Environments: Experience developing systems for harsh field environments. Deployed Robotics: Experience working on robotics deployed in real world settings such as autonomous vehicles, drones, or ruggedized robots. Systems Level Robotics: Fluency across software, electrical, and mechanical systems. Autonomy Software: Knowledge of autonomy stacks used in robotics. As well as how compute performance impacts autonomy algorithms. This position is for our FieldAI Federal Team. This team works on projects connected to the U.S. government which requires U.S. Person eligibility. A U.S. Person as defined by 22 C.F.R §120.62 includes U.S. Citizen, U.S. National, lawful permanent residents (green card holders) refugee or asylee. Compensation The salary range for this role is $70,000-$300,000. The actual offer for this position will be based on factors such as relevant experience, competencies, certifications, and how well the candidate meets the qualifications outlined above. Part of our compensation package also includes full benefits, equity, and generous time off. Field AI Onsite Work Philosophy At Field AI, we believe the most effective way to collaborate and solve complex challenges is by working together in person. This is a fully onsite role, and candidates will be expected to work from our Mission Viejo, CA office. In-person engagement is essential to our success, and we offer flexible working hours to support focus and work-life balance.

FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use. About Us 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. Embedded Systems Engineer In this role you will develop computing systems for humanoid robots. This may span compute platform design (ARM, SoC, microcontrollers), firmware and BSP bring-up, and kernel-level Linux work. Work will focus on a robot payload that intakes LiDAR, camera, IMU, and tactile sensor information and then outputs joint manipulation and locomotion commands that let the robot stand, move, and use its hands. You will partner closely with the ML team building the robot's software brain, ensuring the compute platform can run their perception and manipulation models with the latency and throughput they need. The system is designed to operate across a diversity of humanoid robot platforms, so your work will generalize across different hardware rather than target a single robot. You will collaborate closely with the mechanical, electrical, and ML teams to build tightly integrated, safety-conscious solutions ready for deployment in the field. What You Will Get To Do 1. Backpack Compute Platform Compute Platform Design: Design and select the embedded compute platforms (ARM, SoC, microcontrollers) that power the humanoid payload, balancing capabilities against SWaP constraints. Firmware & BSP Bring-Up: Write and customize bare-metal and RTOS firmware, board support packages (BSPs), and bootloaders for the humanoid payloads computing hardware. Kernel-Level Development: Work at the Linux kernel level to support real-time performance and reliable operation of the backpack's compute stack. Testing & Diagnostics: Conduct thermal profiling, power draw analysis, and latency measurement, and implement watchdogs and health checks for the compute stack. 2. Sensor & Actuator Drivers Perception & State Sensor Drivers: Adapt, integrate, and where needed develop drivers for cameras, LiDAR, and IMUs that feed the backpack's compute platform with real-time perception and state-estimation data. Motor, Joint & Tactile Drivers: Adapt, integrate, and where needed develop drivers for motors, joint actuators, and tactile sensors, supporting low-latency control and feedback for humanoid manipulation and locomotion. Communication & Timing: Bring up wired (Ethernet, CAN, GMSL, SPI, I2C) and wireless interfaces with deterministic timing (PTP, PPS) across the payload. 3. Manipulation & ML Integration ML Team Partnership: Partner closely with the ML team building the robot's software brain to ensure the compute platform meets their latency, memory, and throughput needs. Manipulation Data Pipeline: Build the data pipeline connecting camera, LiDAR, IMU, and tactile input to joint manipulation commands, from raw sensor capture through to actuator control. Edge ML Enablement: Support accelerated inference on the backpack so ML models can interpret sensor data and issue robot commands in real time. ROS/DDS Middleware: Expose driver and sensor data through ROS/ROS2 and DDS interfaces so the ML team's software brain can consume it in real time. 4. Cross-Platform Generalization & Collaboration Platform Abstraction: Design the backpack's compute and software architecture to generalize across a diversity of humanoid robot platforms. Cross-Team Collaboration: Work closely with mechanical, electrical, and sensor engineers to develop a tightly integrated backpack payload. Technical Leadership: Lead the technical direction of backpack compute development, from architecture decisions through implementation. Safety & E-Stops: Implement e-stop circuitry and safety monitoring on the backpack platform, laying the groundwork for functional safety as the fleet matures. What You Have Education: B.S., M.S., or Ph.D. in Computer Engineering, Electrical Engineering, Robotics, or a related field. Experience Level: Minimum of 3+ years of hands-on experience with embedded systems.. We welcome candidates across mid-level to senior and staff levels. Programming: Proficient in C++ and Python for embedded and application-level development. Embedded Systems Experience: Experience bringing up and customizing bare-metal and RTOS firmware, Linux kernel and device drivers, and board support packages (BSPs), across platforms such as Jetson or custom SBCs. Driver Development: Experience developing drivers for cameras, LiDAR, IMUs, tactile sensors, or motors, connecting sensors and actuators to embedded compute. ML/Edge Acceleration: Familiarity with GPU, TPU, or NPU offload and frameworks such as CUDA or TensorRT for edge inference, ideally supporting manipulation or perception models. Real-Time Communication Protocols: Hands-on experience with Ethernet, CAN/CAN-FD, SPI, I2C, UART, USB, or PCIe, wireless links, and timing protocols such as PTP. ROS & Middleware: Familiarity with ROS/ROS2 and DDS for exposing sensor and actuator interfaces to higher-level software. SWaP-Constrained Design: Experience designing compute hardware and firmware under tight size, weight, and power (SWaP) constraints, such as wearable or backpack-style payloads. What Will Set You Apart Humanoid Robotics Experience: Experience developing embedded systems, firmware, or drivers for humanoid or other legged robot platforms. Manipulation & Robot Control Knowledge: Familiarity with joint manipulation, motor control, and how sensor data flows into robot commands such as standing or grasping. Kernel-Level Development: Experience with Linux kernel modules, device driver development, kernel-level debugging, PREEMPT_RT, and deterministic, low-jitter timing in production systems. Safety-Critical Systems: Experience implementing e-stop circuitry, safety monitoring, or other safety-critical embedded systems for robots operating near people. Experience with functional safety standards such as ISO 13849 or ISO 10218 for robots operating in human environments. ML Collaboration: Experience working directly with ML or perception teams to meet model latency, memory, and throughput requirements on embedded hardware.

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. Hardware Team: The Hardware Team at Field AI develops perception and compute payloads that power autonomous robotics systems in complex real-world environments. Our work spans the full hardware stack designing and integrating sensing systems (LiDAR, camera, TOF, IMU, GPS), embedded compute (CPUs, GPUs, microcontrollers, Linux, ROS), electrical systems (power distribution, communication), and mechanical components (structures, thermal regulation, ingress protection). The team focuses on both development (research, design, prototyping, testing) and operations (production, testing, QA, debugging). We’re a small, fast-moving team, and we care deeply about improving: 1) core capabilities, 2) system reliability, 3) system scalability. As a growing team we are also building operational systems and procedures from the ground up. Embedded Compute Role: As an Embedded Compute Engineer on the Hardware Team at Field AI, you will contribute to the architecture, configuration, and validation of the compute systems that serve as the backbone for our robotic platforms. Your work will span low-level firmware, Linux-based configuration, and system performance analysis across ARM and x86 SBC platforms. From firmware on microcontrollers to ROS data streams on SBCs, you’ll ensure the entire compute stack is optimized, reliable, and robust under field conditions. You will collaborate closely with the sensor, electrical, and autonomy teams to build tightly integrated solutions ready for deployment in challenging field environments. Additionally, while your focus will be on computing systems you will likely contribute across all hardware domains. What You Will Get To Do 1. Compute System Design Compute Architecture: Architect and configure embedded compute platforms (ARM/x86, SBCs) for robotic applications including evaluation, testing and selection. Firmware & Software: Set up and customize Linux environments (Ubuntu, Yocto, JetPack), middleware (ROS), and I/O interfaces. Systems Integration: Integrate compute with sensing and robotic systems. Analyze thermal, power, and bandwidth constraints to meet deployment and runtime requirements. 2. Compute System Implementation Communications: Bring up sensors and peripherals using a range of protocols (USB, Ethernet, GMSL, I²C, SPI, CAN). Data Pipelines: Build and maintain drivers, ROS nodes, and data acquisition pipelines for new hardware components. Systems Configuration: Create configuration files, launch scripts, and firmware update workflows. Testing: Conduct system-level tests such as thermal profiling, latency measurement, and power draw analysis. Documentation & Budgets: Maintain flashing procedures, I/O maps, and debug kits. Manage compute and I/O budgets. 3. Compute System Production & Servicing Build: Work with vendors to procure compute hardware. Develop QA checks for incoming units. Support payload integration and scaling. Debug: Support root-cause analysis for boot, connectivity, and throughput issues. Diagnostics Monitoring: Implement watchdogs, health checks, and other evaluation tools. Monitor compute system performance across CPU, GPU, memory, I/O, and networking. What You Have Education: B.S., M.S., or Ph.D. in Computer Engineering, Robotics, Electrical Engineering, or a related field. Experience Level: We are recruiting across a wide range of experience levels from entry level engineers to senior and staff engineers. Embedded Systems: Experience with embedded platforms (Jetson, Raspberry Pi, x86 NUCs, custom SBCs). Linux: Proficiency with Linux system configuration, scripting, and headless deployment tools. Firmware: Strong skills in firmware development for microcontrollers, including bare-metal and RTOS environments. Programming: Proficient in C++ and Python for embedded and application-level development. Communication Protocols: Experience with USB, Ethernet, I²C, SPI, CAN, GMSL, and similar interfaces. ROS Ecosystem: Familiarity with ROS, device drivers, TF, and data streaming/publishing. Debugging: Comfort with hardware/software debugging tools (oscilloscopes, logs, power monitors, analyzers). Systems Thinking: Ability to diagnose and optimize across compute, thermal, timing, and I/O layers. What Will Set You Apart

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. Who are We? Field AIis 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 At FieldAI, we build autonomous robotic systems that operate in demanding, real-world environments where tight integration between hardware and software is critical. We’re looking for a Sensor Systems Engineer to support system and component level design, integration, and validation for sensing systems on wheeled robotic platforms across both federal and commercial programs. Sensor Systems Role: As a Perception Systems Engineer on the Federal Team, you will contribute to the design, integration, calibration, and validation of the sensing and compute systems that underpin our autonomy stack. You will work with a diverse array of sensors—LiDARs, depth cameras, IMUs, GPS, and more—ensuring each one delivers accurate, time-synchronized, and spatially consistent data in a range of environments and operating conditions. You will collaborate closely with the autonomy, compute, electrical, and mechanical teams to build tightly integrated solutions ready for deployment in challenging field environments. Additionally, while your focus will be on sensors you will likely contribute across all hardware domains. What You Will Get To Do 1. Sensor System Design Sensor Architecture: Work across hardware and software teams to define sensing requirements. Identity, test, and select sensors such as LiDARs, depth cameras, GPS, IMUs, ToF, and other devices. Systems Integration: Integrate sensors with electrical (USB, Ethernet, I2C, CAN, GMSL), mechanical (mounts, jigs, isolation), and software (configurations, drivers, ROS nodes) systems. Ensuring power, thermal, and protocol compatibility. Spatial Performance: Architect system to meet spatial sampling performance requirements including spatial coverage, range, resolution, and transform accuracy. Temporal Performance: Implement and validate synchronization strategies, triggering schemes, timestamp encoding, and end-to-end latency minimization. 2. Sensor System Implementation Performance Characterization: Evaluate sensor performance (spatial resolution, temporal drift, EMI noise, sync errors etc.). Test under real-world environmental conditions (vibration, lighting, moisture, temperature). Calibration: Design and execute both intrinsic and extrinsic calibrations. Build alignment rigs and calibration boards as needed. Optimization: Tune sensor configurations (exposure, gain, filtering, frame rate, etc.) and processing pipeline (filtering etc.) for optimal performance Documentation: Create timing diagrams, sensor maps, coordinate transforms, and maintain all configuration files, launch scripts, driver references, and firmware states. 3. Sensor System Production & Servicing Build: Work with vendors to procure sensors. Develop QA checks for incoming units. Support payload integration and manufacturing at scale. Debug: Conduct root cause analysis of sensor systems including issues across hardware and software boundaries. Monitor: Develop protocols for monitoring the sensing system health, data quality, and calibration status during field deployments. What You Have Education: B.S., M.S. or Ph.D. in Robotics, Electrical Engineering, Engineering Physics, Physics, or a related field. Experience Level: We are recruiting across a wide range of experience levels from entry level engineers to senior and staff engineers. Hands-On Sensors Experience: Hands-on work with perception sensors such as LiDAR, depth cameras, IMUs, GPS. Systems Thinking: Cross-functional collaboration experience across electrical, mechanical, and software teams. Sensor Physics: Strong foundation in optics, signal processing, and electromagnetic wave propagation. Lab Skills: Hands-on testing, calibration, and debugging skills (oscilloscopes, logs, vibration/thermal setups) Communication Protocols: Experience with protocols such as USB, Ethernet, GMSL, CAN, I2C, and CSI. Computer & Software: Experience working with ROS/ROS2, sensor drivers, coordinate transforms (TF), and timing protocols (PTP, NTP, etc.). Timing & Triggers: Experience with timestamping, synchronization, triggering, and latency constraints. Calibration & Characterization: Experience designing and executing intrinsic, extrinsic, and temporal calibrations, along with sensor characterization under real-world environmental conditions. Simulation: Experience high-fidelity simulation environments (Gazebo, Isaac Sim, RViz) for sensor modeling. What Will Set You Apart Scaling: Experience taking systems from prototype to large scale production. Field Environments: Experience developing systems for harsh field environments. Deployed Robotics: Experience working on robotics deployed in real world settings such as autonomous vehicles, drones, or ruggedized robots. Systems Level Robotics: Fluency across software, electrical, and mechanical systems. Autonomy Software: Knowledge of autonomy stacks used in robotics. As well as how sensor performance impacts autonomy algorithms.

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. About the Job The Infrastructure Security Engineer will secure the cloud infrastructure and deployment platforms powering FieldAI’s autonomous robotic systems. You will work closely with engineering teams to design, assess, and improve the security of large-scale distributed systems operating in production environments. This is a hands-on engineering role focused on Kubernetes security, cloud-native infrastructure, CI/CD systems, software supply chains, identity and access management, and production deployment platforms. Your work will directly impact the reliability, resilience, and security of critical infrastructure supporting real-world autonomous system operations.