The Role

Mach Industries is seeking a Senior Operational Performance Engineer to track vehicle performance and uncertainty from conceptual design through production and to lead the evidence strategy that closes the gaps. You will maintain the vehicle-level picture of predicted performance, measured performance, and the confidence each claim deserves. You will define the engineering questions that matter most, determine what analysis and test evidence is needed to answer them, and drive measured-data insights back into the conceptual design and MDAO tools that generate the next prediction.

This is a vehicle-level engineering role. You will work across Conceptual Design, MDAO, GNC, Propulsion, Mechanical, Flight Test, and other engineering teams to track performance, identify risks, define evidence requirements, establish assessment criteria, and drive uncertainties toward closure. You will work closely with the Mass Properties and Vehicle Performance engineer, whose records and baselines feed your tracking and assessment work.

This role is part of Operational Performance within Mach's Vehicle Design and Performance organization, alongside Conceptual Design and MDAO. Conceptual Design creates, MDAO enables, and Operational Performance assesses and closes the loop. The ideal candidate combines broad vehicle knowledge with strong experimental judgment and a track record of independently defining what a program needs to learn and influencing how it gets there.

Key Responsibilities

• Own vehicle-level performance tracking from conceptual design through production, maintaining a continuous picture of predicted performance, measured performance, and the deltas between them as the vehicle matures.
• Own vehicle-level uncertainty tracking, quantifying confidence in each performance claim, prioritizing the highest-consequence unknowns, and driving them toward closure.
• Lead vehicle performance assessment and evidence planning across the development lifecycle, scaling rigor from early demonstrators through production commitments.
• Translate performance objectives, requirements, and engineering risks into analysis plans, measurement requirements, data quality needs, and success criteria.
• Define what must be measured, under what conditions, and to what confidence to produce the required evidence, and recommend tests to Flight Test and discipline teams accordingly.
• Establish pre-test predictions and uncertainty expectations, then assess ground and flight test results against those benchmarks to determine what has been learned and what remains open.
• Partner with Flight Test and discipline teams to make data requirements practical and achievable, explaining engineering intent and prioritizing needs.
• Partner with MDAO and Conceptual Design to feed model correlation results, validated data, and prediction-accuracy trends back into design and sizing tools, improving fidelity and reducing uncertainty on future vehicles.
• Communicate vehicle performance state, open uncertainties, evidence status, and risk-informed recommendations to Vehicle Leads, engineering teams, and program stakeholders.
• Build and maintain reusable methods and automated workflows for performance tracking, assessment, model correlation, and reporting.

Required Qualifications

• Bachelor's degree in Aerospace Engineering, Mechanical Engineering, or a related technical field.
• 5+ years of experience in aerospace vehicle performance assessment, flight test analysis, test engineering, experimental engineering, or a closely related discipline.
• Demonstrated ownership of performance tracking, evidence strategy, or model correlation for complex aerospace vehicles or physical systems.
• Experience maintaining a vehicle- or system-level performance picture over time, including tracking predicted-versus-measured deltas and confidence as a design matures.
• Strong understanding of vehicle performance and the interactions among mass properties, aerodynamics, propulsion, structures, power, controls, and vehicle configuration.
• Experience assessing experimental, ground test, or flight test data against performance predictions or engineering models.
• Experience using Python, Julia, MATLAB, or similar tools for technical analysis and data processing.
• Proven ability to influence cross-functional teams and collaborate effectively across engineering disciplines.
• Ability to communicate technical findings, risks, assumptions, and recommendations clearly to engineering teams and program stakeholders.

Preferred Qualifications

• Master's degree in Aerospace Engineering, Mechanical Engineering, or a related field.
• Experience with aircraft, UAS, missiles, rockets, or other aerospace vehicles through flight test or operational assessment.
• Experience with flight test instrumentation, telemetry, test planning, or experimental design.
• Experience mentoring engineers in performance assessment methods, evidence standards, or uncertainty management.
• Experience building automated data-processing, analysis, or validation workflows.
• Familiarity with conceptual design, vehicle sizing, MDAO, or multidisciplinary vehicle analysis, including experience feeding test-derived corrections back into design tools or models.

This role determines how Mach knows whether its vehicles are performing as intended and ensures that every test makes the next design better. Your tracking and evidence strategy will connect predictions to measurements and drive the resulting insights back into the tools that shape Mach's next vehicle.

Additional Requirements