Senior Control Systems Engineer, Vehicle Dynamics & Abstraction (m/f/d)
This listing is for a Senior Control Systems Engineer, Vehicle Dynamics & Abstraction (m/f/d) role at Quantum-Systems GmbH, in Gilching, Bayern, Germany. The listing describes it as a full-time, senior position.
DGJ summary of this job
Our own short read of this listing, built only from the facts it gives. The employer’s original text follows further down.
This listing is for a Senior Control Systems Engineer, Vehicle Dynamics & Abstraction (m/f/d) role at Quantum-Systems GmbH, in Gilching, Bayern, Germany. The listing describes it as a full-time, senior position.
The advert mentions Python, C++ and MATLAB among the skills and tools for this role.
The employer does not state a salary in this listing; DGJ Insight below shows an official pay benchmark for the place where one exists.
Benefits mentioned in the advert: paid time off.
Visa sponsorship is not mentioned. Applicants from outside Germany should check the official work permit route before applying.
Dev Global Jobs found this job on Arbeitnow on Nov 7, 2026.
- Employer
- Quantum-Systems GmbH
- Location
- Gilching, Bayern, Germany
- Job type
- Full-time
- Level (from the title)
- senior
- Pay
- Not stated by the employer
- Found
- Nov 7, 2026 on Arbeitnow
- Employer text
- 531 words, about 2 min to read
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DGJ Insight
Our own data about this role and place, from official statistics and our live job index.
Source: OECD Average annual wages, 2025
- EU Blue Card: Recognised degree and a job offer above the salary threshold
- Skilled worker visa (Fachkräfte): Recognised qualification and a job offer
- Opportunity Card (Chancenkarte): Points-based job search for up to one year
Official routes: Make it in Germany (Federal Government portal)
About the role
Full text from the employer, as published on Arbeitnow, arranged into sections. Nothing added or removed.
We are seeking a Senior Control Systems Engineer to lead the design and execution of robust control layers across a highly diverse fleet of autonomous vehicles. In this role, you will act as the critical boundary layer to the upper autonomy stack. As the industry transitions toward End-to-End driving models, your primary mandate is to ensure that high-level motion commands are executed sensibly and strictly safeguarded at the physical limits of the vehicle.
Your designs will address complex, real-world scenarios rather than idealized environments. You will build control architectures that remain robust under severe, highly non-linear real-world conditions. This includes handling sudden tire slip, navigating challenging terrain such as mud, gravel, potholes, and dense vegetation, maintaining stability on steep inclines and side slopes, and delivering predictable tracking despite asymmetric system degradation, such as a damaged mechanics.
01What is your Day to Day Mission
Control Architecture Abstraction: Maintain a standardized, platform-agnostic motion command interface that cleanly abstracts underlying mechanical complexity from the planning layers.
Multivariable Control & Allocation: Design and deploy control laws to manage path tracking, velocity execution, and actuator saturation, incorporating data-driven control allocation to dynamically distribute effort across multiple actuators.
System Identification & Modeling: Utilize data-driven system identification techniques to model unknown plant dynamics, latencies, and actuator responses.
Pragmatic Simulation & Verification: Validate control loops rapidly. If filter design and linear/nonlinear analysis indicate a controller will behave, you are empowered to rely on lean, pragmatic subsystem simulations to iterate fast rather than being bottlenecked waiting for massive, full-system high-fidelity simulation runs.
Motion Safeguarding: Ensure that incoming motion commands are dynamically evaluated, bounded, and safeguarded against the physical realities and constraints of the vehicle chassis in real time.
02What you bring to the team
Experience: Proven professional experience developing and deploying real-time closed-loop control systems.
Linear & Classical Control Design: Deep foundational command of classical control theory, including frequency-domain loop-shaping, stability margin analysis (Bode/Nyquist), and standard state-space design methods (LQR/pole-placement).
System Identification & Allocation: Demonstrated experience utilizing system identification methods or empirical frequency response estimation to characterize raw plant dynamics, alongside data-driven control allocation techniques.
Nonlinear Control Theory: Strong theoretical and practical foundation in Differential Geometry as applied to nonlinear systems, specifically utilizing Feedback Linearization and Differential Flatness for exact state transformation.
State Estimation: Proficiency in Kalman Filtering for state estimation under non-holonomic constraints.
Implementation & Tooling: High proficiency in either the MATLAB/Simulink, C++, or Python. The core requirement is your ability to translate complex control logic into clean, deterministic execution ready for real-time environments.
03Your Benefits
Direct impact: See your contributions rapidly integrated from cutting-edge research into industrialized products, flying in the field within short development cycles.
Culture & Environment: A dynamic, fast-paced, and collaborative startup environment with flat hierarchies, efficient collaboration, and a strong emphasis on continuous learning opportunities.
Work-life Balance: We offer flexible work schedules, and 30 days of paid vacation each year to support your personal and professional life.
Lunch Benefit: We promote healthy eating and the well-being of our employees with a monthly lunch budget.
Health & Wellness: We support your physical well-being with a company-subsidized eGym Wellpass membership, giving you access to thousands of gyms and sports facilities.
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