Remote | Control System Engineer - $30-$50/hour

This a Full Remote job, the offer is available from: New York (USA)

We are sharing a specialised consulting opportunity for experienced Control System Engineers with strong expertise in PID control, plant modelling, controller design, Python-based control development, and real-system deployment to contribute to an advanced AI training and engineering-evaluation project.

Selected professionals will design and evaluate controllers for physical systems, build and validate plant models, implement control algorithms using open-source technical stacks, and apply practical engineering judgement to real-world control scenarios. No prior experience in AI is required.

Key Responsibilities

Controller Design & Tuning

• Design and tune PID controllers for physical systems

• Apply modern control methods such as LQR, MPC, or Kalman filtering

• Select control strategies appropriate to system dynamics and performance requirements

• Evaluate stability, responsiveness, robustness, and real-world operating behaviour

• Refine controller parameters based on measured system performance

Plant Modelling & System Identification

• Develop plant models from first principles and empirical system data

• Apply state-space and transfer-function modelling techniques

• Validate mathematical models against real-world measurements

• Identify modelling assumptions, uncertainties, and performance limitations

• Refine models as additional system data becomes available

Control Software & Technical Implementation

• Implement control algorithms in Python using open-source engineering libraries

• Work with tools such as python-control, SciPy, CasADi, do-mpc, Julia ControlSystems, or OpenModelica

• Debug and validate control code across realistic engineering scenarios

• Translate mathematical control strategies into reliable technical implementations

• Maintain clear and reproducible control-development workflows

Real-System Deployment & Performance Analysis

• Deploy and evaluate controllers on robotics, drones, automotive, industrial, or comparable physical systems

• Analyse system behaviour under realistic operating conditions

• Identify performance limitations, instability, or unexpected responses

• Iterate on controller and model design to improve real-world operation

• Apply practical judgement beyond simulation-only results

Engineering Evaluation & Collaboration

• Document control strategies, engineering decisions, and technical assumptions clearly

• Provide structured feedback on control-system designs and outputs

• Review engineering approaches for technical accuracy and practical feasibility

• Collaborate remotely with interdisciplinary technical contributors

• Contribute domain expertise to AI training and engineering-evaluation workflows

Ideal Profile

• Bachelor's degree or higher in Control, Electrical, Mechanical, Mechatronics, Aerospace Engineering, or a closely related field

• 5+ years of post-degree hands-on controller-design experience

• Proven experience deploying control systems on real hardware rather than simulation-only environments

• Strong practical expertise with PID control

• Experience implementing at least one modern control approach such as LQR, MPC, or Kalman filtering

• Strong plant-modelling skills using first-principles and data-driven methods

• Experience with state-space and transfer-function techniques

• Fluency in Python for control development, debugging, and validation

• Familiarity with open-source control and optimisation tools

• Strong system-performance analysis and troubleshooting ability

• Excellent written and verbal English communication skills

• Master's or PhD-level training is advantageous

• Experience with CasADi, do-mpc, Modelica/OpenModelica, Julia, system identification, embedded C/C++, ROS, or nonlinear, robust, or adaptive control is beneficial

• Publications or open-source contributions in relevant technical areas are also valuable

• No prior AI-training or model-evaluation experience is required

Engagement Details

• Independent contractor engagement

• Fully remote

• Compensation: $30-$50/hour

• Work will involve controller design, PID tuning, plant modelling, real-system deployment, Python-based control development, and technical evaluation

• Strong hands-on experience deploying controllers to physical systems is central to this engagement

• Assignments may involve robotics, drones, automotive platforms, industrial hardware, or comparable dynamic systems

• Technical environments may include Python control libraries, optimisation frameworks, Modelica tools, Julia, ROS, or embedded systems

• Project scope, workload, control scenarios, and evaluation standards may evolve depending on project requirements

• Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

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