Summer Research Program Intern 2027, Tactical Autonomy (Group 10-03)

MIT Lincoln Laboratory•Lexington, MA

1d•$44•Onsite

About The Position

The Tactical Autonomy Group develops and delivers AI-enabled autonomy and robotic systems where it counts—at the tactical edge. As an FFRDC, we combine academic depth in algorithms, controls, and machine learning, the execution speed of industry, and direct mission pull from operational end-users to solve problems others can’t. We don’t stop at papers: we design, build, integrate, field-test, and transition autonomy stacks—spanning perception, decision-making, learning, and control—into real operations across the DoD and Intelligence Community. The Tactical Autonomy Group is seeking summer interns to help develop the next generation of autonomous and robotic systems for challenging real-world environments. Interns work alongside multidisciplinary teams of engineers and researchers and contribute directly to algorithm development, software implementation, simulation, hardware integration, and field experimentation. Depending on background and project needs, internship opportunities may include: Robotics and autonomous systems: Develop and integrate autonomy algorithms spanning perception, state estimation, planning, decision-making, guidance, and control for uncrewed air, ground, and maritime systems. AI/ML and perception: Develop robust approaches for object detection, recognition, tracking, sensor fusion, and learning that operate in complex environments and on resource-constrained edge platforms. Planning and multi-agent autonomy: Develop optimization, decision-making, coordination, and task/mission-planning algorithms for individual autonomous systems and heterogeneous teams or swarms. Embedded autonomy: Develop high-performance software and integrate autonomy algorithms with embedded compute, sensors, communications, and robotic hardware under real-time and size, weight, and power constraints. Modeling, simulation, and experimentation: Build simulation environments and autonomy test infrastructure; evaluate autonomous agents across realistic operational scenarios; and transition algorithms from simulation to hardware and field experiments. Projects span fundamental research through prototype development and field testing. Interns are encouraged to work across disciplinary boundaries, and specific assignments will be matched to individual interests, experience, and ongoing program needs.

Requirements

Currently pursuing a BS, MS, or PhD in Aerospace Engineering, Mechanical Engineering, Electrical/Computer Engineering, Computer Science, Robotics, Physics, Mathematics, or a related technical field.
Strong programming and software-development skills, with experience in one or more languages commonly used for robotics and autonomy, such as C++, Python, MATLAB, Julia, or similar.
Strong technical foundation in one or more relevant areas such as robotics, controls, estimation, perception/computer vision, machine learning, optimization/planning, embedded systems, or modeling and simulation.
Ability to work effectively on multidisciplinary teams and apply technical skills to new and unfamiliar problems.
Strong written and verbal communication skills.
U.S. citizenship is required.

Nice To Haves

Prior research, project, competition, or internship experience involving robotics, autonomous systems, AI/ML, embedded systems, or related technologies is desirable but not required.

Responsibilities

Develop and integrate autonomy algorithms spanning perception, state estimation, planning, decision-making, guidance, and control for uncrewed air, ground, and maritime systems.
Develop robust approaches for object detection, recognition, tracking, sensor fusion, and learning that operate in complex environments and on resource-constrained edge platforms.
Develop optimization, decision-making, coordination, and task/mission-planning algorithms for individual autonomous systems and heterogeneous teams or swarms.
Develop high-performance software and integrate autonomy algorithms with embedded compute, sensors, communications, and robotic hardware under real-time and size, weight, and power constraints.
Build simulation environments and autonomy test infrastructure; evaluate autonomous agents across realistic operational scenarios; and transition algorithms from simulation to hardware and field experiments.