Control System Engineer

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This is a fully remote position open to candidates based in United States.

Pay: $30$50/hr

Role Title: Control System Engineer

Role Type: Contractor

Location: Remote

We are engaging Control System Engineers to contribute their advanced technical expertise to an exciting customer project focused on real-world control this role youll apply your expertise to help train next-generation AI systems. Your work will shape how models learn reason and perform through high-quality real-world input. No prior experience in AI is required your domain knowledge is what matters. This opportunity is ideal for professionals passionate about shipping robust controllers modeling complex plants and applying both classical and modern control strategies in tangible environments.

Scope of Work

1. Design and tune PID and advanced controllers (e.g. LQR MPC Kalman Filters) for deployment on physical systems such as robotics drones automotive or industrial hardware.
2. Develop plant models from first principles and validate them against empirical data using state-space and transfer function methodologies.
3. Implement and verify control algorithms in Python using open source toolkits (e.g. python-control SciPy CasADi do-mpc Julia ControlSystems OpenModelica).
4. Document engineering decisions and control strategies with clear high-quality written communication and engage in effective verbal discussions as required.
5. Analyze system performance identify areas for improvement and iterate on design for optimal real-world operation.
6. Collaborate remotely with interdisciplinary contributors while maintaining autonomy and technical independence.

Preferred Qualifications

1. Bachelors degree (or higher) in Control Electrical Mechanical Mechatronics or Aerospace Engineering.
2. Over 5 years of hands-on controller design experience post-degree with proven real system deployment (not simulation-only).
3. Proficiency in building and validating physical plant models using first principles and data-driven methods.
4. Demonstrated delivery of both classical (PID) and at least one modern control method (LQR MPC or Kalman) on real hardware.
5. Fluency in Python for control code development debugging and validation using open source stacks.
6. Exceptional written and verbal English communication skills focused on clarity and precision.
7. Additional strengths such as a Masters or PhD production MPC with tools like do-mpc or CasADi Modelica/OpenModelica modeling Julia proficiency system identification embedded C/C ROS nonlinear/robust/adaptive control or contributions to publications/open source are valued.

How to apply

Apply here with your profile. We will then email you a link to complete your application on the hiring platform your application is only considered once that final step is done.