Propulsion Engineer - Modeling & Simulation job opportunity at Destinus.

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Date2026-02-18T08:14:03.427Z bot
Destinus Propulsion Engineer - Modeling & Simulation
Experience: 3-years
Pattern: Full-time
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loacation Payerne, Switzerland
loacation Payerne....Switzerland

About the role Imagine shaping how propulsion systems are analyzed, validated, and optimized long before physical testing begins. At Destinus, we develop advanced propulsion systems where performance, reliability, and rapid iteration are critical. To support this mission, we are looking for a Propulsion Engineer who will focus on building analytical and AI-driven tools to model, analyse, and predict rocket motor behaviour. In this role, you will work at the intersection of propulsion engineering, data science, and software development. You will help create modern modelling frameworks that combine physics-based methods with artificial intelligence approaches such as neural networks, surrogate models, and data-driven optimization. Your work will directly support design decisions, performance estimation, and development speed for rocket motor programs. At Destinus, we are revolutionizing the defense industry with cutting-edge Unmanned Aerial Vehicles (UAVs). Our innovative technologies are designed to meet the unique demands of modern defense operations, delivering unparalleled speed, precision, and cost effectiveness. Destinus partners with government agencies and defense organizations worldwide to provide advanced solutions for mission-critical operations, enabling a new era of efficiency and technological superiority. Join us in shaping the future of defense with groundbreaking aerospace innovations What you'll do Design, develop, and maintain analytical software tools to model rocket motor performance, internal ballistics, and system-level behavior Develop and validate data-driven models using simulation results and experimental test data Collaborate closely with propulsion and systems engineers to translate engineering requirements into robust, usable software tools Create scalable and reusable Python-based libraries for analysis, modeling, and visualization Implement AI-integrated frameworks, including neural networks, surrogate models, and regression-based approaches, to accelerate design and analysis workflows Support uncertainty quantification, sensitivity studies, and design space exploration using automated and AI-assisted methods Document software tools, modeling assumptions, and validation results to ensure traceability and long-term usability Continuously improve tool performance, usability, and reliability based on user feedback and evolving project needs What You’ll Need Bachelor’s or Master’s degree in Software Engineering, Aerospace Engineering, Mechanical Engineering, or a related field 1–3 years of professional experience in software development, scientific computing, or data analysis Strong proficiency in Python, including experience with scientific and data-focused libraries (e.g. NumPy, SciPy, pandas, PyTorch, TensorFlow, scikit-learn, or similar) Experience developing analytical models, simulation tools, or data-driven applications Solid understanding of numerical methods, modeling, and algorithm development Ability to write clean, maintainable, and well-documented code Strong analytical mindset and willingness to learn complex physical systems Background or hands-on experience in rocketry, propulsion, or aerospace systems, is a plus. Nice to have familiarity with rocket motor physics, internal ballistics, or thermofluidic, would be considered a plus. Experience with surrogate modeling, reduced-order models, or physics-informed machine learning, would be considered a plus. Experience with version control (e.g. Git) and collaborative software development workflows, would be considered a plus. Who You Are You enjoy breaking complex physical problems into models that work in the real world, and you are comfortable operating between theory, data, and hardware. You move fast, iterate faster, and are not afraid of imperfect first versions when they lead to better outcomes. You take ownership of your work, question assumptions, and continuously push for stronger, more effective solutions. You thrive in multidisciplinary teams where engineering decisions truly matter and where your contributions directly impact real systems, not just concepts  

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