Careers at Field Ai

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. What You'll Get to Do 1. Own End-to-End Robot Verification & Validation Design and execute verification and validation strategies for complete robotic systems, from individual capabilities through full autonomous missions Develop clear acceptance criteria, performance metrics, and test methodologies for new robot capabilities Validate system behavior across multiple robotic platforms, environments, and operating conditions Build repeatable qualification and regression processes that allow new capabilities to ship without compromising existing functionality Establish a clear understanding of what “deployment-ready” means and provide quantitative evidence that systems meet that bar. 2. Build Scalable Robotics Test Infrastructure Develop automated test infrastructure spanning simulation, hardware-in-the-loop, lab testing, and full robot operation Create reusable test scenarios and evaluation frameworks that exercise autonomy under nominal, edge-case, and failure conditions Build tools for experiment execution, telemetry collection, automated analysis, visualization, and reporting Improve the reproducibility of robot testing so failures can be recreated, diagnosed, and verified efficiently Help move validation from individual one-off tests toward continuously running, scalable system evaluation 3. Validate Real-World Robot Behavior Design tests that expose robots to the uncertainty and variability encountered in real deployments Exercise systems across changing terrain, obstacles, environmental conditions, sensor degradation, communication failures, compute limitations, and other realistic disturbances Evaluate not only whether a robot succeeds, but how reliably, safely, and consistently it behaves across repeated trials Identify performance boundaries and characterize where system behavior begins to degrade Work directly with physical robots in the lab and field to reproduce difficult system-level failures 4. Turn Failures Into Engineering Signal Debug failures across autonomy, sensing, state estimation, planning, control, system integration, compute, networking, and hardware boundaries Use telemetry and experimental data to isolate root causes rather than simply identify symptoms Develop tooling and instrumentation that make complex robot behavior easier to understand Convert field failures and difficult-to-reproduce issues into deterministic regression tests whenever possible Partner with subsystem owners to verify fixes and prevent recurrence 5. Drive System Reliability and Release Readiness Partner closely with autonomy, robotics software, hardware, systems, and field teams throughout the development lifecycle Identify integration and reliability risks early and ensure they are represented in the validation process Build dashboards, scorecards, and automated evaluations that provide a clear view of system health and capability maturity Help define release gates based on measurable system performance rather than subjective readiness Continuously improve the V&V process as the autonomy stack, robot platforms, and deployment environments evolve

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.

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, ROS, sensor drivers), 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. Sensor Systems Role: As a Sensor Systems Engineer on the Hardware Team, you will contribute to the design, integration, calibration, and validation of the sensing 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

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.

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 robots reconstruct and interact with the physical world to unprecedented levels. This asks for an unprecedented user experience. Therefore, we are hiring a 3D/AR/VR Software Engineer in support of our humanoid UI/UX team. In this role, you will implement, integrate, maintain, and support AR/VR applications that enable supervision, manipulation, and locomotion capabilities for humanoid robots. You will help turn new robotic capabilities into reliable, maintainable, user-facing systems that can be deployed, evaluated, and operated on real robots. Your work will span design, prototyping, UI implementation, and robot integration, user-study-based evaluation. You will draw on your expertise on input and interaction design, rendering, to build innovative 3D interfaces for robotics.

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 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 Our Field Foundation Model (FFM) powers a global fleet of autonomous robots that capture massive streams of multimodal data across diverse, dynamic environments every day. As part of the Insight Team our mission is to transform this raw, multimodal data into actionable insights that empower our customers and engineers to deliver value. Field-insight Foundation Model (FiFM) is at the core of how we transform multimodal data from autonomous robots into actionable insights. As an AI/ML Engineer on the FiFM team, you will drive research and model development for one of Field AI’s most ambitious initiatives. Your work will span computer vision, vision-language models (VLMs), multimodal scene understanding, and long-memory video analysis and search, with a strong emphasis on agentic AI (tool use, memory, multimodal retrieval-augmented generation).This is a full-cycle ML role: you’ll curate datasets, fine-tune and evaluate models, optimize inference, and deploy them into production. It’s a blend of applied research and engineering, requiring creativity, rapid experimentation, and rigorous problem-solving. While FiFM is your primary focus, you’ll also contribute to broader perception and insight-generation initiatives across Field AI.

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.

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, Data Pipelines, you will design and build the systems and integrations that help move data reliably from robots in the field to the teams and services that depend on it — analytics, autonomy, ML training, and deployment operations. You will collaborate with cross-functional teams spanning robotics, autonomy, and deployment to build the data backbone of a field robotics company.