Senior MDAO Engineer

About the company

Mach provides a full-stack autonomy platform that enables off-road equipment OEMs to deploy driverless, AI-powered machinery across agriculture, defense, landcare and other rugged industries.

About this role

ABOUT MACH INDUSTRIES Founded in 2022, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. THE ROLE Mach Industries is seeking a Senior MDAO Engineer to help develop and apply the multidisciplinary design, analysis, and optimization methods used to size, evaluate, and mature vehicles across Mach's product suite. This role sits at the intersection of vehicle configuration, sizing, mission performance, operational data, and analytical tool development. You will work with configuration, performance, test, and discipline engineering teams to improve the models and workflows used to evaluate vehicle concepts and understand mission capability. You will also directly support trade studies, sizing studies, and performance assessments as needed in a fast-moving, multidisciplinary environment. The ideal candidate combines strong aerospace engineering judgment, practical vehicle design intuition, and the ability to develop, modify, and validate engineering analysis tools. KEY RESPONSIBILITIES - Develop and apply MDAO models, methods, and workflows for conceptual and preliminary vehicle design. - Support vehicle sizing, configuration trades, mission analysis, and performance assessments across Mach's product suite. - Improve analytical tools used to evaluate vehicle concepts, including models for aerodynamics, propulsion, mass properties, structures, controls, mission performance, and operational constraints. - Partner with configuration, sizing, performance, test, and discipline engineering teams to ensure MDAO workflows reflect real design needs and produce decision-relevant outputs. - Incorporate higher-fidelity analysis, ground test data, flight test data, and operational performance data to improve model accuracy and future design decisions. - Conduct optimization studies, sensitivity analyses, and trade studies to identify key design drivers and communicate implications to engineering stakeholders. - Help define assumptions, constraints, objectives, and figures of merit for vehicle-level design studies. - Maintain effective analytical workflows using practical software development practices, including version control, documentation, reproducibility, and basic testing. - Mentor engineers contributing to or using MDAO workflows, particularly around modeling assumptions, trade study setup, and interpretation of results. - Contribute to the technical roadmap for MDAO capability, balancing near-term design support with longer-term model and workflow improvements. REQUIRED QUALIFICATIONS - Bachelor's degree in Aerospace Engineering, Mechanical Engineering, or a related technical field. - 5+ years of relevant aerospace engineering experience, or an advanced degree with significant relevant experience in vehicle design, MDAO, sizing, configuration development, performance analysis, or computational design. - Experience with aircraft, UAS, missile, spacecraft, or other aerospace vehicle sizing, configuration trades, mission analysis, or performance assessment. - Broad understanding of how aerospace disciplines influence vehicle design, including aerodynamics, propulsion, mass properties, structures, controls, and mission performance. - Experience developing or modifying engineering analysis tools using Python, MATLAB, C++, Julia, or a similar language. - Ability to set up and interpret trade studies, optimization studies, sensitivity analyses, or design-of-experiments. - Strong engineering judgment and ability to communicate assumptions, limitations, tradeoffs, and recommendations clearly. - Experience working in fast-paced, multidisciplinary engineering environments. PREFERRED QUALIFICATIONS - Advanced degree in Aerospace Engineering, Mechanical Engineering, Applied Mathematics, or a related field. - Experience with UAV, aircraft, missile, or defense product development. - Experience in conceptual design, preliminary design, configuration/sizing, mission performance, or operational performance analysis. - Experience incorporating test, flight, or operational data into engineering models. - Experience with MDAO, optimization, surrogate modeling, uncertainty analysis, or multidisciplinary trade-space exploration. - Experience with OpenMDAO, pyOptSparse, Dymos, GPkit, SUAVE, in-house MDAO frameworks, or similar tools. - Experience helping define analytical workflows, model validation practices, or design study best practices. Disclosures This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (EAR) and the International Traffic in Arms Regulations (ITAR).  Please note that any offer for employment may be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations without sponsorship for an export license. Mach participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offers may vary based on (but not limited to) work experience, education and training, critical skills, and business considerations. Highly competitive e