AI Robotics Engineer Jobs

View detail

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.

View detail

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.

View detail

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.

View detail

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.

View detail

Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. 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.

View detail

Develop state-of-the-art navigation and sensor fusion algorithms for UAVs, design and implement GNC and flight control systems, build filtering and estimation strategies for robust and efficient flight performance, run extensive simulations including Monte Carlo, SITL, HITL, and coverage testing, analyze test flight data and refine algorithmic performance, support full-stack system integration including GNSS, INS/IMU, localization, and fusion, and maintain and evolve a flight-proven flight computer across multiple UAV platforms.

View detail

As a SLAM / Multi-View Geometry Engineer on the Robotics team, you will develop systems that enable robots to perceive, track, and reconstruct the world in 3D from multi-camera and multimodal sensor data. You will work on real-time and offline SLAM pipelines used during teleoperation and robot data collection, as well as scalable systems for reconstructing and tracking 3D structure from large datasets. Specific responsibilities include developing and deploying online SLAM systems used during robotic data collection with multi-camera sensor stacks and teleoperation platforms, building systems for large-scale 3D reconstruction and point tracking across massive datasets, working with research and engineering teams to scale multi-view geometry pipelines to large datasets, improving the accuracy, robustness, and scalability of perception systems used in robotics data collection and training pipelines, and collaborating across robotics, perception, and ML teams to integrate geometry-based methods with learned models.

View detail

As a Perception Engineering Intern at Hayden AI, the responsibilities include taking ownership of a real project and seeing it through to completion, building and shipping features with support from senior engineers, writing clean and scalable code, testing work and iterating quickly, being involved in all phases from design discussions to deployment, collaborating with engineers in code reviews and team discussions, participating in standups, sprint planning, and retrospectives, supporting the team on ad hoc engineering tasks, helping improve performance, reliability, or usability where needed, and asking questions, seeking feedback, and applying it quickly. Deliverables or project examples may include GPS data analysis, training deep learning models, creating AI datasets, lidar/camera data tooling, test cases for end-to-end system performance, developing a cloud service in the event processing pipeline, and adding a page or new user flow to the Portal web application.

View detail

The role involves defining and building next-generation CPU networking architecture for datacenter and emerging robotics/automotive applications. The engineer will contribute to current datacenter networking efforts while helping to seed and specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingestion, with an initial focus on datacenter networking and robotics in the automotive/robotics space. The position requires working at the intersection of Network on Chip (NoC) design, performance modeling, and RTL design to guide architectural decisions and collaborating across hardware, software, and systems teams to define and refine networking requirements. The responsibilities also include driving forward next-generation CPU networking architecture for AI/ML workloads and taking early-stage automotive/robotics networking concepts from seeding and specification through to project initiation.

View detail

The role involves defining and building next-generation CPU networking architecture for datacenter and emerging robotics/automotive applications, contributing to current datacenter networking efforts, and helping to seed and specify future medium- to low-power robotics/automotive devices for AI/ML compute and sensor ingest. Responsibilities also include working at the intersection of Network-on-Chip (NoC), performance modeling, and RTL design to guide architectural decisions, collaborating across hardware, software, and systems teams to define and refine networking requirements, and driving forward next-generation CPU networking architecture for AI/ML workloads.