About the role Integer Technologies is seeking an Autonomous Systems Engineer to support the design, development, and deployment of advanced autonomy software for maritime robotic platforms. This role spans the autonomy stack—including perception, localization, mapping, planning, and control—with an emphasis on developing robust algorithms for real-world operation in constrained and uncertain environments. Ideal candidates have experience in robotics, state estimation, controls, simulation, or related fields, along with strong software development skills and an interest in solving challenging multidisciplinary problems. Candidates must be U.S. citizens eligible to obtain a DoD security clearance and enjoy working closely with engineers, scientists, and academic collaborators. Because Integer is a fast-moving research and development organization, this role is intentionally broad. We occupy a unique position in the research ecosystem—close enough to academia to co-develop new methods with university partners, and close enough to operational users to transition those ideas into fielded technology. Engineers in this role move between software development, modeling and simulation, field experimentation, technical analysis, collaboration with research partners, and contributions to future programs. Don't meet every qualification? Please apply anyway. We are seeking engineers with deep expertise in one or more technical areas and an interest in collaborating across disciplines. We welcome applicants ranging from early-career engineers with strong technical foundations to experienced researchers and developers. Responsibilities, project ownership, and technical leadership will grow with experience and demonstrated capability. What you'll do Algorithm Development & Implementation Develop and evaluate algorithms for autonomy, estimation, planning, and control on simulated and physical robotic systems. Depending on project needs, this may include system identification, sensor fusion, machine learning, multi-agent coordination, or data reduction techniques that enable operation under bandwidth, storage, and compute constraints. Modeling & Simulation Build and validate models of robotic platforms, sensors, operating environments, and communications systems. Use simulation, Monte Carlo analysis, and hardware-in-the-loop testing to characterize performance, quantify uncertainty, and identify failure modes before field deployment. University Collaboration Serve as a technical point of contact for academic partners, helping define collaborative research, evaluate technical approaches, and translate research outcomes into program deliverables. Verification & Data Analysis Design and execute computational studies, laboratory experiments, and field evaluations. Analyze experimental data, compare results with model predictions, and use findings to improve algorithms and system performance. Technical Communication Produce clear technical reports, interface and design documentation, and program deliverables. Contributing to conference or journal papers with university partners is supported and encouraged. Required Qualifications Must be a U.S. Citizen with the ability to obtain and maintain a U.S. DoD Secret Clearance. Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering or a related technical field; advanced degrees preferred. Demonstrated depth in at least one and working familiarity with at least two of the following: Dynamics, control theory, and vehicle kinematics/dynamics modeling System identification, parameter estimation, and model validation State estimation and sensor fusion (Kalman-family filters, particle filters, factor graphs) Modeling, simulation, and hardware-in-the-loop test methods Machine learning applied to physical systems — learned dynamics or sensor models, data-driven estimation, and learning-based control or decision-making Data reduction and representation — compression, feature extraction, and dimensionality reduction under bandwidth, storage, or compute constraints Autonomous decision-making under uncertainty (planning, POMDPs, learning-based methods, multi-agent coordination) Experience applying those methods to fielded or prototype engineered systems in maritime, aerospace, ground, space, industrial, or other complex multi-domain systems. Proficiency in Python and/or C++, and comfort with a scientific computing environment such as MATLAB/Simulink, Julia, or the Python scientific stack. Ability to engage critically with technical literature and research methods — evaluating assumptions, derivations, and the sufficiency of results in support of stated conclusions. Understanding of autonomy frameworks, decision-making algorithms, and real-time system constraints in distributed, multi-agent environments. Excellent collaboration and communication skills, with the ability to interface across multidisciplinary teams and external partners. Desired Qualifications We do not expect any one candidate to bring all of these. If you are strong in the core areas above and several of these are unfamiliar, we would still like to hear from you! Autonomous Systems & Robotics Experience with autonomous surface vessels (ASVs), autonomous underwater vehicles (AUVs), or other uncrewed platforms. Experience with robotics simulation environments such as Isaac Sim, Gazebo, MOOS-IvP, HoloOcean, Stonefish, DAVE, or Unreal/Unity-based simulators. Experience with Robot Operating System (ROS/ROS2) or real-time middleware such as DDS, Zenoh, or MQTT. Knowledge of distributed systems, multi-agent coordination, or swarm autonomy. Familiarity with sim-to-real transfer, domain adaptation, or training with limited real-world data. Dynamics, Controls & Intelligent Systems Guidance, navigation, and control (GNC), flight dynamics, spacecraft attitude determination, or flight test experience. Optimization methods including MPC, trajectory optimization, convex optimi