AI/ML Engineer - Multidisciplinary Engineering Design Associate Staff

1w1 week ago

MIT Lincoln Laboratory

Lexington, US · Full-time · $116,400 – $182,200

About this role

The Structural & Thermal-Fluids Engineering Group provides innovative multidisciplinary engineering solutions for underwater, ground, air, and space-based prototype systems for national security applications. Examples include structural-material systems for space-based imaging, thermal management from cryogenic to hypersonic, and aerodynamic designs for UAVs and hypersonic platforms. Engineering solutions utilize high-fidelity models, multidisciplinary simulations, environmental testing, and advanced materials.

Group 74 seeks engineers combining AI/ML algorithm development with engineering modeling expertise in fluids, structures, or thermals. Engineers support simulation, design, optimization, and test activities across applications from low-speed aircraft to hypersonic systems and satellites. The Group employs machine learning to improve physics-based simulations like aerodynamic analysis for accelerated conceptual design.

Engineers enhance existing methods and implement cutting-edge AI/ML techniques for rapid, accurate concept design in complex multidisciplinary problems. The successful candidate joins an interdisciplinary team developing operational prototype hardware across the full program lifecycle from concept to fielding and testing. The position involves collaboration with leading experts on challenging engineering problems.

This role offers contributions to cutting-edge research and innovative solutions for national security. Opportunities include working on diverse prototypes facing performance, size, weight, and environmental challenges. The position may require special security clearances and travel to meetings and field sites.

Requirements

M.S. in Aerospace Engineering, Mechanical Engineering, Computer Science, or related; B.S. with three years’ experience also considered
Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications
Proficiency in C++, Python, MATLAB, or similar for algorithm development and software integration
Experience applying engineering software to design and analysis, e.g., fluid, structural, or thermal simulations
Ability to work within an interdisciplinary team
Ability to clearly communicate results in oral presentations and written reports
Experience with high-performance computing (HPC) environments for large-scale simulations
Experience implementing multidisciplinary design optimization (MDO) frameworks

Responsibilities

Develop and apply novel artificial intelligence and machine learning algorithms to engineering applications such as physics-informed machine learning, data-driven surrogate modeling, reinforcement learning, or agentic AI
Support simulation, design, optimization, and test activities for systems ranging from low-speed aircraft to hypersonic platforms and satellite design
Employ machine learning methods within modeling suite to improve physics-based simulations like aerodynamic analysis
Enhance existing AI/ML methods and implement cutting-edge techniques to enable rapid and accurate concept design
Contribute to development of operational prototype hardware spanning full program lifecycle from concept development to fielding and testing
Utilize engineering software for fluid, structural, or thermal simulations in multidisciplinary engineering solutions