Senior Digital Twin Engineer — Vehicle & Mission Modeling

Key working interfaces

Works under the Head of AI Sensor Fusion & Digital Twin and partners directly with the Senior AI Sensor Fusion Engineer. Sensor Fusion supplies current observations and confidence; Digital Twin maintains models and predictions. Planning and driving/flight autonomy teams use those predictions for authorized movement decisions. The Flight Simulation team owns simulator execution, interfaces, timing and scenarios; domain engineers supply discipline expertise.

What you’ll do

• Define vehicle and mission model states, parameters, interfaces, configuration identity, validity ranges and measurable prediction criteria with the relevant engineering teams.
• Build physics-based, reduced-order, data-driven or hybrid models for assigned vehicle, energy, payload and mission behavior, choosing fidelity appropriate to the intended decision and available measurements.
• Work directly with the AI Sensor Fusion Engineer to update the digital twin from fused onboard and external information, including timestamps, units, data confidence and missing-input handling.
• Provide predictions and scenario comparisons that help planning and autonomy engineers evaluate driving and flight options, energy requirements, operating limits and mission changes.
• Compare predicted and observed behavior, identify model parameters, quantify uncertainty and investigate discrepancies with sensor-fusion and domain engineers.
• Implement maintainable model software and interfaces with appropriate numerical stability and execution performance for engineering evaluation and assigned onboard uses.
• Validate model behavior using independent measurements, replay and controlled ground/flight test evidence; work with the simulation team to integrate models into repeatable scenarios.
• Maintain model versions, calibration records, validation evidence and clear limits of use as vehicle configurations and mission requirements evolve.
• Establish and continually improve digital-twin evaluations using independent measurements, prediction-error and uncertainty metrics, repeatable benchmarks and regression tests; expand coverage when model discrepancies reveal gaps and document the conditions in which results are valid.

Required qualifications

• Bachelor’s degree in aerospace, mechanical, electrical or controls engineering, applied mathematics or a related field, or equivalent practical expertise.
• Typically 5+ years developing digital twins, dynamic-system models, system-identification methods or scientific software correlated with physical measurements; equivalent depth demonstrated through delivered work is also considered.
• Strong understanding of dynamic-system modeling, differential equations, numerical integration, parameter estimation and model verification.
• Experience updating models from sensor or fused time-series data, with correct units, timestamps, configuration identity and measurement uncertainty.
• Experience using predictive models to evaluate operating choices, performance, energy or mission feasibility and validating predictions against independent measurements.
• Proficiency in Python and at least one production modeling environment such as MATLAB/Simulink, Modelica or C++, including maintainable model interfaces and debugging.
• Demonstrated ability to quantify prediction uncertainty, diagnose differences between models and measurements, and balance fidelity, execution cost and validity for a defined use.

Preferred qualifications

Experience with vehicle or aircraft digital twins, mission modeling, energy prediction, autonomous-system integration, physics-informed or hybrid models, reduced-order modeling, FMI/FMU co-simulation and real-time execution. Experience working closely with sensor-fusion, planning, controls and simulation teams.

AI tools and automation: Strongly preferred where programming is a substantial part of the role: hands-on use of Claude Code, OpenAI Codex, Cursor, GitHub Copilot or equivalent tools for development, debugging, test automation, code review or analysis scripts. Include relevant Python, MATLAB or other scripting experience. Provide a specific example, your contribution, any measured time saved or quality improvement, and how you verified the result. Equivalent tools are welcome.

We welcome transferable experience from related industries. You do not need to meet every preferred qualification. Tell us what you have delivered and how your skills apply to this role.

Location & working arrangements

Eagle Field Airport · 11100 W Eagle Ave, Firebaugh, CA 93622

Eagle Field Airport is our primary development and manufacturing location. Palo Alto area or remote arrangements may be considered for engineering work that does not require hands-on access. All current openings require availability to participate in development and flight-testing activities at Eagle Field Airport from time to time, with advance coordination. Flight-test roles require on-site availability for preparation and campaigns. Scheduling and travel arrangements will be discussed for each role.

About ASKA

At ASKA, we are on a mission to build the world’s first AI sensor fusion and digital twin system that manages autonomous driving and autonomous flying in one vehicle. We are bringing ground and air autonomy together to support the warfighter—moving critical supplies, reaching people in need, and reducing exposure in dangerous environments. Our team works across aircraft engineering, intelligent software, electric propulsion, and advanced manufacturing, with development and testing at Eagle Field Airport in California. Bring your expertise. Take ownership. Help build technology that matters.

ASKA welcomes applicants with diverse backgrounds and relevant experience. For questions or application accommodations, message the recruiting team.