Careers at 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. 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.

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. Manufacturing Engineer, Robotics Hardware The Manufacturing Engineer will be responsible for designing, implementing, and continuously improving assembly and manufacturing processes for Field AI products. This individual will serve as the bridge between Engineering and Manufacturing, ensuring products are designed for manufacturability, assembly, testability, and long-term scalability. The ideal candidate is highly hands-on, thrives in fast-paced hardware development environments, and has experience bringing complex electromechanical products from prototype through production. This role will play a critical part in improving product yields, reducing assembly complexity, establishing quality standards, and developing functional test strategies that ensure reliable field performance. What You Will Get To Do 1. Manufacturing Process Ownership Own the development, implementation, and continuous improvement of assembly processes for robotic systems, payloads, and subassemblies. Create and maintain manufacturing work instructions, assembly procedures, process flows, and build documentation. Design assembly workflows that optimize throughput, quality, ergonomics, and repeatability. Lead manufacturing readiness activities for prototype, pilot, and production builds. Support contract manufacturers and internal production teams with process development and troubleshooting. 2. Design for Manufacturing (DFM) & Design for Assembly (DFA) Partner closely with Mechanical, Electrical, and Systems Engineering teams during product development. Drive DFM and DFA reviews throughout the product lifecycle to reduce manufacturing complexity, cost, and assembly time. Identify opportunities to simplify assemblies, reduce part count, improve tolerance stack-ups, and increase manufacturability. Provide feedback on component selection, fabrication methods, and assembly approaches to improve product robustness and scalability. 3. Yield Improvement & Production Support Establish manufacturing KPIs and yield tracking systems. Analyze production data to identify root causes of defects, failures, and inefficiencies. Lead failure analysis and corrective action (FACA) initiatives to improve process capability and product quality. Drive continuous improvement projects focused on yield, cycle time, labor efficiency, and cost reduction. 4. Quality & Test Development Define manufacturing quality requirements and inspection strategies for components, assemblies, and finished products. Develop acceptance criteria, inspection plans, and quality checkpoints throughout the manufacturing process. Establish functional test requirements and validation procedures for payloads, subsystems, and completed systems. Collaborate with Engineering and Quality teams to develop automated and semi-automated test solutions where appropriate. Ensure manufacturing processes consistently produce products that meet performance and reliability requirements. 5. Tooling, Fixtures & Automation Design and implement assembly fixtures, tooling, and manufacturing aids to improve consistency and efficiency. Evaluate opportunities for automation and process optimization. Develop calibration and maintenance requirements for manufacturing equipment and test stations. Ensure production tools and fixtures are documented and controlled. What You Have Bachelor's degree in Manufacturing Engineering, Mechanical Engineering, Electrical Engineering, or a related field. 3+ years of manufacturing engineering experience supporting complex hardware products. Strong experience with DFM, DFA, process development, and production support. Experience developing assembly processes for electromechanical systems. Knowledge of manufacturing quality systems, root cause analysis, and process control methodologies. Experience creating manufacturing documentation, work instructions, and process validation plans. Strong analytical and problem-solving skills with a data-driven approach to decision making. What Will Set You Apart Experience in robotics, autonomous systems, aerospace, automotive, industrial equipment, or similar industries. Experience supporting products from prototype through scaled production. Familiarity with PCBAs, wiring harnesses, sensors, motors, actuators, and precision mechanical assemblies. Experience developing production test equipment and functional test procedures. Knowledge of GD&T, tolerance analysis, SPC, Lean Manufacturing, and Six Sigma methodologies. Experience working with contract manufacturers and external production partners

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.

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. Mechanical Systems Role: As a Mechanical Engineer on the Hardware Team at Field AI, you will contribute to the design and implementation of mechanical systems that house and support sensing and compute platforms in real-world environments. From ruggedized enclosures to thermal management to manufacturability, your work will be critical to ensuring our systems operate reliably in the field. Responsibilities may span the full lifecycle from CAD through production to field support. You will collaborate closely with electrical, compute, and systems engineers to build tightly integrated solutions ready for deployment in challenging field environments. Additionally while your focus will be on mechanical systems you will likely contribute across all hardware domains. What You Will Get To Do 1. Mechanical System Design Structures: Design and model mechanical structures including external enclosures, internal compute frames, and load-bearing chassis. Mounts: Design and validate robust sensor mounts, payload attachment points, and mechanical interfaces. Ingress Protection: Implement IP-rated solutions with gaskets, seals, membranes, and coatings to meet water/dust ingress standards. Thermal Management: Incorporate thermal mitigation strategies such as fans, heat sinks, conductive paths, and airflow guides. Mass & Volume Budgets: Ensure adherence to payload constraints, including tight volumetric envelopes and weight limitations. 2. Mechanical System Implementation CAD & Simulation: Build detailed SolidWorks CAD assemblies. Run FEA and thermal simulations to validate strength, durability, and heat dissipation. Material & Component Selection: Choose materials and components to meet mass, strength, thermal, and manufacturability constraints. Design for Production: Apply DFM, DFA, DFS principles throughout the design lifecycle. System Testing: Conduct mechanical load testing (shock, vibration), thermal validation, ingress tests, and sensor alignment assessments. Prototyping: Rapidly iterate on prototypes for fit checks, thermal evaluations, and integration trials. Documentation & Budgets: Generate mechanical drawings, GD&T annotations, BOMs, and assembly instructions for fabrication and QA. Manage weight, volume, and thermal budgets. 3. Mechanical System Production & Servicing Build: Work with vendors and contract manufacturers to procure mechanical hardware. Develop QA checks for incoming units. Support payload integration and scaling. Debug: Investigate mechanical failures, deformation, and environmental weaknesses during testing and deployments. Monitor: Develop protocols for monitoring the system mechanical health and loads. What You Have Education: B.S., M.S., or Ph.D. in Mechanical Engineering, Mechatronics, or related field. Experience Level: We are recruiting across a wide range of experience levels from entry level engineers to senior and staff engineers. CAD Expertise: Proficient with SolidWorks or equivalent mechanical CAD platforms. Thermal & Structural Analysis: Familiarity with FEA and thermal modeling tools. Field-Ready Design: Experience designing hardware that survives vibration, shock, thermal cycling, and environmental exposure. Manufacturing Knowledge: Experience designing for CNC, sheet metal, additive manufacturing, and assembly workflows. Mechanical Systems Integration: Experience working across teams to integrate mechanical systems with compute, sensors, and power electronics. Lab Skills: Comfort with mechanical debugging, thermal test setups, vibration tables, and ingress testing. Cross Functional Robotic Skills: Ability to contribute electrical, sensing, and embedded computing work to deliver robust integrated systems. What Will Set You Apart

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. 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.

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 Software Engineer to support testing, deployment, and integration of wheeled robotic platforms across both federal and commercial programs As a Robot Autonomy Engineer - Software at Field AI, you’ll be at the forefront of bringing our autonomous systems to life in the real world, owning deployment, integration, and ongoing performance in the field. This role is equal parts engineering and problem-solving. You’ll work hands-on with both customers and our internal teams to ensure successful operations, rapidly incorporate field feedback to improve reliability and performance, and drive adoption so our systems become mission-critical from day one. If you thrive in fast-paced, high-impact environments and want to see your work directly enable the future of autonomy, this is the role where you’ll make it happen. What You’ll Get To Do Drive strategic integration, debugging, and rapid capability development while providing essential software support Build robust utilities and tools to facilitate integration and automated testing for system software builds Provide high-level technical expertise and analytical insights to advance the development of robust software architectures What You Have PhD degree in Robotics, Computer Science, Electrical Engineering, or a related field or MS degree in a related field with 2+ years of industry or applied research Proven expertise in software engineering across the full program lifecycle, with a focus on early-stage system design and development. Experience/Familiarity with robotics middleware such as ROS / ROS 2 or similar distributed robotics software systems Experience/Familiarity with distributed systems (multiple nodes, real-time comms) Experience/Familiarity with embedded systems (C/C++ on constrained hardware) Ability to work effectively across adjacent domains, including software, electronics, networking, and mechanical interfaces Proven track record managing complex programs with multiple dependencies in agile/hybrid frameworks Excellent written and verbal communication skills; comfortable presenting to executives and diverse audiences Strong analytical capabilities, with experience in financial modeling, ROI analysis, and tracking KPIs Ability to thrive in fast‑paced, high‑growth startup environments; proactive, adaptable, resilient The Extras That Set You Apart Experience deploying, operating, or maintaining mission-critical systems in real-world environments. Experience using Jira or Wrike or Confluence or other program management software tools Ability to work directly with customers in high-stakes, fast-paced settings, translating needs into technical solutions. Excellent communication skills, with the ability to explain technical concepts to non-technical users. Willingness to travel and work on-site with customers as needed.

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 Field AI is building the future of autonomy, from rugged terrain to real-world deployment. We are on a mission to develop intelligent, adaptable robotic systems that operate beyond simulation and thrive in unpredictable environments. As our Robotics Autonomy Engineer – Planning and Control, you will design, implement, and deploy advanced motion planning and control algorithms that enable our robots to move with precision, robustness, and efficiency across diverse environments. You will work on navigation, trajectory generation, and motion control for robotic platforms ranging from wheeled and legged systems to complex humanoid architectures. If enabling robots to navigate challenging, dynamic environments excites you, and you want to work where your code works in the physical world - this is your role. This is Field AI. What You’ll Get To Do 1. Develop Robust Motion Planning Algorithms Design, develop, and refine motion and navigation planning algorithms for challenging real-world scenarios such as narrow passages, dynamic obstacles, and complex environments. Design optimization-driven approaches for path and trajectory generation that ensure smooth, reliable, and efficient robot navigation across modalities. Ensure scalability, reusability, and adaptability of planning approaches across diverse deployment contexts. 2. Advance Control and Planning Integration Develop and tune control algorithms that ensure precise trajectory tracking and stable operation across different robotic systems. Collaborate across autonomy layers to ensure seamless coordination between perception, planning, and control for robust real-world performance. 3. Validate and Test Across the Stack Build and maintain testing pipelines from unit-level validation to full robot deployment. Utilize simulation and testing environments for algorithm evaluation, benchmarking, and regression validation. Analyze real-world telemetry to diagnose issues, identify improvements, and enhance algorithm robustness. 4. Diagnose and Improve Field Performance Investigate and resolve issues arising from field deployments through structured data analysis and debugging. Deliver targeted improvements that address specific challenges while maintaining general-case reliability and performance. What You Have PhD degree in Robotics, Computer Science, Electrical Engineering, or a related field with 2+ years of industry or applied research experience or MS degree in a related field with 4+ years of relevant experience, or BS degree in a related field with 8+ years of relevant experience. Strong understanding of motion planning, trajectory generation, and control systems. Experience developing algorithms for one or more robotic systems (wheeled, legged, wheeled-legged, humanoid). Familiarity with motion planning libraries like OMPL, MoveIt, Nav2 stack etc Solid programming skills in C++ and Python on Linux-based systems. Familiarity with robotics middleware such as ROS/ROS 2. Experience with robot sensors including LiDARs, stereo/depth cameras, IMUs, GPS, wheel encoders. The Extras That Set You Apart Exposure to real-world deployment of autonomous systems. Background in optimization, control, or numerical methods for trajectory planning. Familiarity with learning-based or hybrid planning approaches. Contributions to open-source planning or control frameworks. Familiarity with safety-critical autonomy and industrial robotics use cases.