Jobs at FieldAI

Own end-to-end global payroll across UCAN, APAC, and EMEA, including employees, contractors, and temporary workers. Manage payroll taxes, filings, year-end reporting, payment processes, worker classification, staffing agencies, EOR partners, payroll systems, integrations, journal entries, accruals, reconciliations, and scalable controls. Partner with People Ops, Legal, leadership, and international teams on payroll implications, employee support, and expansion into new countries.

Leads customer-focused robotics and autonomy programs from planning through deployment and operational handoff. Translates customer requirements into technical plans, manages milestones, risks, dependencies, and tradeoffs, and coordinates engineering, product, operations, support, and customer success teams. Oversees field deployments, operational readiness, customer communication, and issue resolution across software, hardware, systems, data, and operations. Requires technical experience with autonomy or self-driving systems, robotics, embedded systems, and real-time platforms.

Develop and integrate software for humanoid robots by combining perception, planning, locomotion, and manipulation systems. Responsibilities include defining subsystem interfaces, bringing up hardware, calibrating sensors, productionizing research code, building integration tests and diagnostics, optimizing real-time performance, and implementing fault monitoring and recovery. The role also coordinates integration milestones and validates robotic systems across simulation and real-world hardware.

Research and develop active perception systems for real-world robots, including viewpoint planning, information gathering, calibrated confidence, abstention, and vision-language reasoning. The role owns research through hardware experiments and deployment, shapes the technical roadmap, and mentors junior contributors. Candidates should have robotics research expertise, strong publications, experience with vision-language or foundation models, and proficiency in Python, C++, and ROS 2.

Research and develop persistent spatio-temporal robot memory, world models, and physics-aware digital twins for long-term autonomy. Build systems combining learned and physically grounded models for scene understanding, reasoning, planning, change detection, and interaction-based system identification. Apply vision-language and foundation models to spatial reasoning and embodied memory, deploying methods on real robots using Python, C++, and ROS 2.

Conduct original research in robot learning and manipulation for physical robots deployed in real-world environments. Develop and evaluate manipulation capabilities, study skill transfer and failure recovery, design experiments, integrate research with robotic hardware, and collaborate with engineering teams. Document findings and contribute to publications, open-source tools, datasets, or other research artifacts.

Conduct research in embodied AI and robotics, focusing on robot learning, active perception, human-robot interaction, or embodied reasoning. Develop algorithms, evaluate them on physical robots in unstructured environments, analyze field data, and contribute to research publications. Work may involve foundation models, planning, decision-making, language-conditioned robotics, and real-world robot experimentation.

As a ROS Developer, you will develop robotic applications using ROS/ROS2, integrate sensors, implement data processing pipelines, and collaborate on autonomy solutions for real-world applications.

Design and integrate mechanical, electrical, and electromechanical hardware for robotic vehicle platforms. Responsibilities include CAD packaging, PCB design, sensor and compute integration, thermal and structural solutions, actuation and control systems, fabrication, hardware bring-up, debugging, validation, and field deployment support. The role spans the full hardware lifecycle and requires close collaboration across mechanical, electrical, embedded, sensor, and autonomy engineering teams.

Integrate control systems, autonomy software, and payloads onto large wheeled, legged, humanoid, and quadruped robotic platforms. Responsibilities include platform abstraction, robot controls, electro-mechanical integration, sim-to-real validation, SIL/HIL testing, safety systems, charging and docking infrastructure, fleet scaling, and field deployment. The role collaborates across autonomy, manipulation, mechanical, and electrical teams to deliver reliable robots for challenging industrial environments.

As the Lead Functional Safety Engineer, you will design and implement safety systems for autonomous robotic platforms, oversee hardware integration, and validate safety protocols while leading a safety-focused engineering team.

Design, prototype, test, and support rugged mechanical systems for robotic sensing and compute platforms. Responsibilities include CAD assemblies, structural and thermal analysis, sensor mounts, ingress protection, material selection, DFM/DFA, mechanical drawings, GD&T, BOMs, prototyping, shock and vibration testing, thermal validation, vendor coordination, QA, field debugging, and production scaling. The intern will collaborate across mechanical, electrical, compute, and systems engineering teams.

Manage schedules and execution for customer-site robotics deployments involving drones, quadrupeds, and humanoids. Responsibilities include maintaining project plans, tracking risks and milestones, coordinating engineering and operations teams, managing deployment logistics, supporting field testing, triaging issues, communicating with customers, and maintaining deployment documentation. The role requires technical literacy, strong organization, customer-facing coordination, and comfort working in dynamic industrial field environments.

Build and maintain systems software for robotic platforms, integrating onboard compute, sensors, networking, hardware interfaces, device drivers, and vendor SDKs. Develop provisioning, deployment, monitoring, diagnostics, and recovery tools. Debug software-hardware issues, improve reliability through testing and observability, and collaborate across robotics, autonomy, hardware, infrastructure, and deployment teams to deliver field-ready robotic systems.

Deploy, integrate, test, and troubleshoot autonomous wheeled robotic systems in customer environments. Analyze field feedback, improve system reliability, implement monitoring and diagnostics, train customer operators, and collaborate across hardware, software, AI, product, and engineering teams. The role supports federal and commercial programs and requires hands-on work with complex robotic systems, field deployments, and customers.

Deploys, integrates, troubleshoots, and maintains autonomous robotic systems in customer environments. Analyzes field feedback, improves system reliability, builds monitoring and diagnostic tools, trains customer operators, and collaborates with software, hardware, AI research, product, and engineering teams to scale deployment practices.

Develop and train whole-body loco-manipulation policies for humanoid robots, deploy learned behaviors to physical hardware, improve motion retargeting and simulation fidelity, and build scalable evaluation and robot-learning infrastructure. The role bridges research and production engineering across reinforcement learning, simulation, control, perception, and hardware deployment.

Conduct research on humanoid manipulation, loco-manipulation, perception, planning, and control. Design and evaluate robotic systems in simulation or hardware, support robotics foundation-model data pipelines, and integrate manipulation data into learning frameworks. Collaborate with researchers, engineers, teleoperators, and field teams on hardware bring-up and autonomy goals. Contribute to academic publications and conference presentations.

Conduct research on humanoid manipulation, loco-manipulation, perception, planning, and control. Design and evaluate robotic systems in simulation or on hardware, support robotics foundation-model data pipelines, and collaborate on hardware integration, teleoperation, and autonomy. The internship emphasizes embodied intelligence, real-world experimentation, and publishing research in leading robotics venues.

Own failure triage and reliability improvements for deployed autonomous robots. Analyze robot behavior, logs, telemetry, and model outputs; build datasets and evaluation sets; train and fine-tune ML models; and partner with modeling, data, deployment, and robotics teams to validate and ship improvements across real-world sites.