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Appsierra Group is seeking an experienced Control System Engineer for a remote contract role. You will design, tune, and validate robust controllers for physical systems such as robotics, drones, and industrial hardware, using both classical and modern methods.
Strong Python experience and open-source toolchain expertise are essential. The role emphasizes real-world deployment on hardware with plant modeling, validation, and clear documentation.
Contract · Remote
Annual Compensation Equivalent: $57,600-$96,000
Hourly Rate: $30-$50/hr
Annual compensation equivalent is calculated at 40 hours per week across 48 workable weeks per year and is not a guaranteed salary.
We are seeking experienced Control System Engineers to apply advanced control engineering expertise to real-world systems and AI evaluation workflows.
The role focuses on designing, tuning, modeling, implementing, and validating robust control systems for physical applications such as robotics, drones, automotive systems, and industrial hardware.
You will work across classical and modern control approaches, develop plant models from first principles and empirical data, and translate control strategies into implementations suitable for real-world deployment.
No prior AI experience is required. The role is centered on your control engineering expertise and practical experience deploying controllers on physical systems.
Design and tune PID controllers and advanced control strategies such as LQR, MPC, and Kalman filtering.
Develop controllers for physical systems including robotics, drones, automotive platforms, and industrial hardware.
Build plant models from first principles and validate them against empirical data.
Apply state-space and transfer-function modeling methodologies.
Implement and verify control algorithms using Python.
Work with open-source control and modeling tools such as Python Control, SciPy, CasADi, do-mpc, Julia ControlSystems, and OpenModelica.
Analyze real-world system performance and identify opportunities for improvement.
Iterate on controller design to improve stability, performance, and operational reliability.
Document control strategies, engineering decisions, assumptions, and validation results clearly.
Communicate technical findings effectively in written and verbal discussions.
Collaborate remotely with interdisciplinary contributors while maintaining technical independence.
Bachelor’s degree or higher in Control Engineering, Electrical Engineering, Mechanical Engineering, Mechatronics, Aerospace Engineering, or a related discipline.
5+ years of hands-on controller design experience after completing your degree.
Demonstrated experience deploying control systems on real physical hardware, not simulation-only work.
Strong experience developing and validating physical plant models using first-principles and data-driven approaches.
Experience delivering classical control systems such as PID on real hardware.
Experience implementing at least one modern control method, such as:
Linear Quadratic Regulator (LQR)
Model Predictive Control (MPC)
Kalman filtering
Strong Python skills for control development, debugging, simulation, and validation.
Experience with open-source control engineering toolchains.
Excellent written and verbal English communication skills.
Ability to explain technical decisions clearly and precisely.
Additional experience in the following areas is valuable:
Master’s or PhD in a relevant engineering discipline
Production MPC using CasADi or do-mpc
Modelica or OpenModelica
Julia and Julia-based control systems
System identification
Embedded C/C++
ROS
Nonlinear control
Robust control
Adaptive control
Technical publications
Open-source control engineering contributions
Contract engagement
Remote
Compensation: $30-$50/hr
Annual compensation equivalent: $57,600-$96,000 based on a 40-hour workweek and 48 workable weeks per year
Actual earnings depend on hours worked and available project scope