We are looking for control engineers who have put controllers on real hardware and want part-time work from home that uses that experience.

The gist An AI project needs expert input on how controllers, plants and operating conditions behave outside of an idealised simulation. You would build plant models, design and tune controllers, check them against data, and document your reasoning so it can be used to teach and evaluate AI systems. Platforms range from robots and drones to automotive and industrial equipment.

Concretely

- Derive plant models from the physics and check them against measured data (state-space or transfer-function form)
- Design, tune and verify controllers, classical PID through to LQR, MPC and Kalman-filter based approaches
- Implement and debug the algorithms in Python, leaning on open-source tooling where it helps (SciPy and python-control, CasADi with do-mpc, or the Julia and Modelica ecosystems)
- Iterate towards something that works reliably on the real system,



and write it up clearly
- Work with a remote, cross-disciplinary group

Requirements An engineering degree (controls, electrical, mechanical, mechatronics or aerospace), and over five years since graduating spent designing controllers, including getting them running on physical hardware. Hands-on PID experience, at least one modern method (LQR / MPC / Kalman), the skill to build and validate plant models both analytically and from data, strong Python, excellent English, and availability of at least 20 hours a week.

Bonus points for production MPC, Modelica, Julia, system identification, embedded C/C++, ROS, nonlinear/robust/adaptive control, publications or open-source work. Advanced degrees welcome.

Engagement

Remote, independent contractor, 20+ hours a week, $30 to $50 per hour.

Apply through OpenTrain.

📌 Controls Engineer, Robotics, Drones and Industrial Hardware (Remote Contract) (India)
🏢 OpenTrain AI
📍 India