Jobs at FieldAI

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.

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.

Twelve-week internship developing robotics simulation tools for real-to-sim workflows, sensor modeling, scenario execution, log replay, regression testing, metrics, and visualization. The intern will use real robot data and field logs to evaluate simulation fidelity and investigate differences between simulated and real behavior. Responsibilities include software development in Python or C++, collaboration with simulation and autonomy engineers, documentation, and a final technical demonstration.

Execute manual and structured testing of robotic systems in lab and controlled environments. Monitor robot behavior, identify and reproduce bugs, document failures, validate fixes, perform regression testing, and improve QA procedures and checklists. Collaborate with engineering teams to resolve issues and provide real-time feedback on system performance, safety, and reliability.

Develop and deploy perception systems for autonomous robots operating in unstructured, off-road environments. Responsibilities include localization, mapping, SLAM, multi-sensor fusion, sensor integration and calibration, field testing, debugging on physical robots, performance monitoring, and production deployment. The role collaborates with autonomy, controls, platform, research, and field operations teams to deliver robust perception capabilities across multiple robotic platforms and missions.

Build and operate scalable data-platform systems for multimodal robotics and machine-learning datasets. Responsibilities include ingestion, processing, validation, labeling, dataset generation, metadata, lineage, versioning, data quality, observability, and workflow reliability. Partner with ML, robotics, infrastructure, and labeling teams to create reusable platform capabilities supporting large-scale data processing, reprocessing, backfills, training, and evaluation.

Build and automate data-flywheel systems for autonomous robots, converting large-scale robot experiences into high-quality, versioned training datasets. Responsibilities include data processing, filtering, labeling, auto-labeling, offline inference, hard-example selection, validation, reproducible dataset generation, and incremental training-data pipelines. Partner with researchers and platform teams to productionize experimental workflows and improve the cycle from robot deployment to usable ML data.

Design, implement, and deploy motion planning, trajectory generation, and control algorithms for wheeled, legged, and humanoid robots. Develop navigation and optimization approaches, integrate planning with perception and control, build testing pipelines, evaluate algorithms in simulation and field deployments, analyze telemetry, and improve autonomy performance in challenging environments. The role requires strong C++ and Python skills, robotics middleware experience, and familiarity with sensors and planning libraries.

Integrate, debug, deploy, and support autonomous wheeled robotic systems across federal and commercial programs. Build integration utilities and automated testing tools, improve software reliability, analyze system performance, collaborate across hardware and software domains, support customers in the field, and translate operational feedback into technical solutions. The role is fully onsite in Irvine, California and requires U.S. Person eligibility.

Develop and own independent safety systems for wheeled, legged, and humanoid robots. Responsibilities include runtime monitoring, collision avoidance, operating-envelope enforcement, fallback behaviors, watchdogs, hazard analysis, safety cases, and verification through simulation, hardware-in-the-loop testing, and field trials. The role collaborates with planning, control, locomotion, and integration teams to ensure autonomous systems operate safely around people, equipment, and terrain.

Develop and deploy whole-body manipulation and autonomy capabilities for humanoid and quadruped robots. Build model-based and learning-based policies, integrate perception and locomotion, adapt vision-language-action models, and design safe grasping and force-control strategies. Create simulation and evaluation pipelines, address sim-to-real challenges, and validate behaviors on physical robots in laboratory and field environments.

Designs and operates AWS and Kubernetes infrastructure, CI/CD systems, GitOps workflows, and internal developer platforms. The role improves reliability, scalability, observability, deployment velocity, and operational maturity across production systems and data pipelines. Responsibilities include infrastructure as code, monitoring, autoscaling, incident response, debugging across application and infrastructure layers, and partnering with engineering teams on platform standards and developer productivity.

Architect and build the robotics platform enabling FieldAI autonomy systems to run reliably across diverse robots and hardware. Define versioned APIs, robot capability and intent models, middleware, runtime infrastructure, and high-performance data flows. Own latency, throughput, reliability, profiling, tracing, simulation, cloud connectivity, and deployment on physical hardware. Collaborate across autonomy, hardware, infrastructure, and deployment teams while setting technical direction and mentoring engineers.

Leads large, complex customer technology programs from scoping through deployment and operational handoff. Serves as the primary executive customer interface, translates business objectives into program plans, coordinates Technical Project Managers and cross-functional teams, manages budgets, risks, dependencies, governance, and contractual commitments, and drives delivery across product, engineering, solutions, and operations. The role also supports enterprise-scale expansion, stakeholder alignment, and continuous improvement of program-management practices.

Lead development of testing and validation for field-ready AI and robotics systems. Design automated test frameworks, validate reliability and risk-aware behavior, collaborate with engineering to improve models through real-world deployments, and ensure robust, production-quality software for robots operating in the field.

Design, build, and maintain CI/CD, build systems, monitoring, and deployment frameworks; automate infrastructure provisioning; ensure reliability, observability, security, and high availability; collaborate with developers and DevOps to optimize systems and troubleshoot production issues.

Lead the design, implementation, and deployment of control systems for autonomous vehicles, focusing on multi-agent collaboration and real-world applications.

The Embedded Systems Engineer designs and integrates embedded computing systems for robotic platforms, collaborating with teams and ensuring performance in field conditions.

As a Mechanical Engineer, you will design, implement, and validate mechanical systems for robotic platforms, ensuring reliability in real-world environments. Responsibilities include CAD modeling, thermal management, materials selection, and collaboration with cross-functional teams.