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Multidisciplinary Design Optimization Jobs (NOW HIRING)

North Wind

CFD Engineer

Newport News, VA · On-site

This role supports system design and optimization by delivering accurate numerical insights validated against physical models and test data, while collaborating closely with multidisciplinary ...

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How much do multidisciplinary design optimization jobs pay per year?

As of Jun 4, 2026, the average yearly pay for multidisciplinary design optimization in the United States is $139,368.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,000.00 and $136,000.00 per year, depending on experience, location, and employer.
What cities are hiring for Multidisciplinary Design Optimization jobs? Cities with the most Multidisciplinary Design Optimization job openings:
Infographic showing various Multidisciplinary Design Optimization job openings in the United States as of May 2026, with employment types broken down into 76% Full Time, 10% Part Time, and 14% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $139,368 per year, or $67 per hour.
AI/ML Engineer for Multidisciplinary Engineering Design-Associate Staff

AI/ML Engineer for Multidisciplinary Engineering Design-Associate Staff

MIT Lincoln Laboratory

Lexington, MA • On-site

Full-time

Posted 5 days ago

Job description

Job Summary:
MIT Lincoln Laboratory is a leader in innovative engineering solutions for national security applications, and they are seeking an AI/ML Engineer for their Structural & Thermal-Fluids Engineering Group. The role involves developing AI/ML algorithms and engineering modeling expertise to solve complex engineering design problems across various applications, contributing to the development of operational prototype hardware.
Responsibilities:
• Support a broad range of simulation, design, optimization, and test activities.
• Develop innovative simulation capabilities to solve challenging engineering design problems across a broad array of applications ranging from low-speed aircraft to hypersonic systems and satellite design.
• Employ machine learning methods within the modeling suite to achieve significant improvements in physics-based simulation.
• Enhance existing methods and implement new cutting-edge AI/ML techniques to enable rapid and accurate concept design for complex and multidisciplinary problems.
• Contribute to the development of operational prototype hardware, spanning the full program life cycle from concept development to fielding and testing.
Qualifications:
Required:
• M.S. in Aerospace Engineering, Mechanical Engineering, Computer Science, or related. Candidates with B.S. degree with three years’ experience will also be considered.
• Experience developing and applying novel artificial intelligence and machine learning algorithms to solve engineering or scientific applications, such as through physics-informed machine learning, data-driven surrogate modeling, reinforcement learning, or agentic AI.
• 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.
Preferred:
• Experience with high-performance computing (HPC) environments for large-scale simulations
• Experience implementing multidisciplinary design optimization (MDO) frameworks.
• Familiarity with software development best practices, including version control (e.g., Git).
Company:
MIT Lincoln Laboratory is a federally funded research and development center chartered to apply advanced technology to problems of national security. Founded in 1951, the company is headquartered in Lexington, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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