AI Robotics Engineer Jobs

Lead Software Engineer, Advanced Pilot Assistant Software (Autonomy/Robotics) Design, build, and deploy robotic and embedded software that powers advanced pilot assistance systems in production environments. Own autonomy-related features or subsystems from concept through deployment, emphasizing reliability and performance. Write, review, and maintain high-quality Python and C++ code across autonomy, systems, and embedded components. Integrate software with hardware, sensors, and perception or data ingestion pipelines to support autonomous and operator-in-the-loop decision-making. Optimize software for edge compute environments, managing CPU/GPU usage, latency, and implementing appropriate safety mechanisms and fail-safes. Lead testing, validation, and deployment efforts to ensure systems meet safety-critical and mission-critical requirements. Mentor engineers and contribute to technical direction through design reviews, code reviews, and hands-on collaboration. Lead multidisciplinary teams in autonomy, integration, and testing by aligning technical efforts, resolving cross-functional challenges, and driving mission-focused execution while balancing hands-on technical oversight with performance optimization, innovation, and stakeholder communication. Design and implement advanced perception algorithms for object detection, classification, and multi-target tracking across diverse sensors. Integrate data from vision systems, radars, and other sensors using probabilistic and deterministic fusion techniques to generate accurate situational awareness. Develop and refine state estimation algorithms for localization and pose estimation using IMU, GPS, vision, and other sensing inputs. Interpret sensor ICDs and technical specifications to ensure proper data handling and synchronization. Optimize perception pipelines for performance, robustness, and real-time efficiency in simulation and real-world environments. Collaborate closely with autonomy, systems, and integration teams to interface perception outputs with planning, behaviors, and decision-making modules. Validate algorithms using synthetic data, simulations, and field testing. Coordinate with hardware and sensor teams to integrate perception algorithms with onboard compute platforms and sensor payloads. Drive innovation in airborne sensing techniques for unmanned aircraft operating in complex or contested environments. Travel approximately 10-15% of the year to office locations, customer sites, and flight integration events. Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap. Director, Flight Systems Integration (R4711) Lead the development, integration, and deployment of the AI pilot to various defense and commercial platforms, overseeing a multidisciplinary team including software engineers, autonomy developers, and perception engineers to ensure successful integration and optimization for each platform's needs. Responsible for technical strategy, team leadership, and delivery of scalable, reliable autonomy to meet program needs. Lead technical leadership and strategy by managing the integration of AI autonomy, perception, and control algorithms with platform-specific hardware and software systems, establishing best practices for software quality, safety, reliability, performance, and scalability, and championing innovation through research and applied AI/ML techniques. Build, mentor, and retain a diverse and high-performing team while fostering a culture of technical excellence, quality, and accountability, coordinating cross-disciplinary efforts for seamless AI integration within flight systems. Drive engineering execution and technical quality by collaborating with engineers to enhance AI systems, translating business needs into technical plans, owning technical quality outcomes, enforcing engineering standards, implementing development processes, and leading continuous improvement initiatives. Ensure AI pilot customization for specific platform needs, leading platform-specific integration efforts with control systems, sensors, and communication interfaces. Collaborate cross-functionally to align platform requirements with AI capabilities and system design and lead performance optimization and testing through rigorous simulation and flight system tests to validate and ensure AI performance meets or exceeds mission requirements. Design and build intuitive web interfaces for robot data annotation, dataset visualization, and experiment tracking. Utilize data-driven techniques to optimize interfaces for efficiency and fast iteration cycles. Integrate AI models to automate manual tasks. Collaborate with AI researchers, robot operators, and annotators to support new user experiences. Senior Robotics Software Engineer | Manipulation Architect and evolve Gecko Robotics' ROS2-based control framework and planning systems for articulated manipulators. Develop perception-driven motion planning using visual and other sensor inputs. Design closed-loop inspect → analyze → rework workflows. Optimize robotic inspection throughput within active manufacturing lines. Own system-level integration between robot control stack, industrial hardware, and Gecko's inspection software. Support system deployment and validation in production environments. Robotics Software Testing Engineer, Factory Orchestration The role involves leading the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. It includes exploring the intersection of computer vision and robotic control to design systems that allow robots to perceive and interact with objects in dynamic environments. Responsibilities include creating models that integrate visual data to guide physical manipulation, collaborating with a multidisciplinary team to translate concepts into deployable robotic capabilities, researching and developing deep learning architectures for visual perception and sensorimotor control, designing algorithms for manipulating complex or deformable objects with precision, optimizing and deploying prototypes onto robotic hardware, evaluating model performance in simulation and real-world environments for robustness, identifying opportunities to apply advancements in computer vision and robot learning to industrial problems, and mentoring junior researchers while contributing to the technical direction of the research roadmap. Senior Robotics Software Engineer, Mobile Robot Orchestration Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap. Develop and optimize computer vision algorithms for object detection, tracking, and 3D reconstruction. Process and analyze large-scale point cloud data for digital twin applications. Support the integration of robotics frameworks such as ROS into real-time systems. Test and improve system performance in diverse environments. Collaborate with a multidisciplinary team to prototype and deploy innovative solutions. As a System Architect, you own the end-to-end architecture, system definition, and strategic implementation for the entire portfolio of robotic and autonomous defense systems, collaborating closely with executive leadership and technical leads and forming a partnership with the Product Manager. Responsibilities include translating complex strategic goals into system-of-systems designs, defining and championing system architecture strategy across the enterprise, ensuring all systems are correctly sized and verified through simulations and system sizing, guiding major technical investment decisions, coordinating large multidisciplinary engineering organizations, providing technical leadership across mechanical, electrical, software, GNC, ML, and product teams, governing system integration standards and validation processes, managing specification and architecture reviews, and implementing processes to improve requirements traceability, documentation, and validation workflows across engineering. $200,000 – $220,000 YEAR

(USD)