Jobs at FieldAI

Lead and coordinate defense-related robotics projects from conception to deployment. Define milestones, manage budgets and resources, align cross-functional stakeholders, track program metrics, prepare executive communications, and surface and resolve technical, operational, and commercial risks to ensure timely, safe, and scalable robot deployment programs.

Design, develop, and deploy production-grade 3D mapping systems and pipelines. Lead end-to-end field deployment, validation, and customer handoff. Build tooling, benchmark reliability, troubleshoot software/hardware/networking issues, and translate field feedback into engineering improvements to support mission-critical autonomous robot deployments.

Lead planning and delivery of 3D mapping projects, contribute to mapping software development, deploy mapping systems and pipelines, validate algorithms on robots, manage cross-functional teams, track progress with PM tools, mitigate risks, and build documentation and playbooks to scale execution.

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.

Design and implement decision-making frameworks and LLM APIs for robotic autonomy, build semantic scene graph world models, and expand testing and validation with unit and integration tests to ensure safe, reliable autonomous systems.

Work with senior engineers to develop and deploy computationally constrained control schemes for large off-road and resource-limited robots. Tasks include system dynamics modeling, system identification, GPU-accelerated control library optimization, real-world deployment of control algorithms, and designing low-latency safety layers for tele-operated and autonomous modes.

PhD-level research internship developing RL-based locomotion and learned planning for legged robots. Design and evaluate sim-to-real training pipelines, build GPU-accelerated simulations, test on real hardware, and translate research into deployable systems while collaborating across perception, systems, and embedded teams.

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

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.

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

The Robot Autonomy Engineer at Field AI supports deployment, integration, and performance of autonomous robotic systems, collaborating with customers and teams to enhance reliability and drive adoption.

As an AI/ML Engineer, you will develop multimodal AI models, focusing on computer vision and agentic capabilities. Responsibilities include data curation, model training, evaluation, and deployment while working with real robotic systems.

The MLOps Engineer will design and maintain infrastructure for machine learning systems in robotics, focusing on deployment, monitoring, and optimization of ML workflows.

Lead large-scale, customer-focused robotics and autonomy programs. Drive cross-functional execution and manage project risks and communications to ensure successful outcomes.

Develop and maintain robotic user workflows, integrating sensors and designing autonomous systems for real-world applications, ensuring high performance and reliability.

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.

As a DevOps Engineer, you will improve CI/CD pipelines, manage containerized infrastructure, ensure deployment reliability, and troubleshoot production issues.

The Software Engineer focuses on building and maintaining development environments and tooling infrastructure to support engineering teams, improving developer velocity and code quality across projects.

The Forward Deployed Engineer will manage deployment, integration, and operational performance of autonomous robotic systems, collaborating with teams and ensuring mission-critical functionalities.