Control System Engineer

SaidGig; New York (NY); Remote; USD 41,000 - 69,000; Full time

Job summary

SaidGig seeks a senior control engineer to design and tune PID and advanced controllers for real-world hardware. You will build high-fidelity plant models and validate them against measurements, while implementing algorithms in Python using open-source toolchains.

Responsibilities include performance analysis, iterative improvement, and precise documentation with clear written and verbal communication. Remote collaboration across disciplines is essential.

Qualifications

• Degree in control, electrical, mechanical, mechatronics, or aerospace engineering.
• 5+ years hands-on controller-design experience on real systems.
• Experience designing PID controllers and validating with first-principles and data.
• Experience delivering PID control and LQR/MPC/Kalman on real hardware.
• Python proficiency for control-code development and validation.
• Strong written and verbal English communication.

Responsibilities

• Design and tune PID and advanced controllers for physical systems.
• Develop plant models from first principles and validate with data.
• Implement and verify control algorithms in Python using open-source tools.
• Analyze system performance, identify improvements, and iterate designs.
• Document control strategies and engineering decisions clearly.
• Collaborate remotely with interdisciplinary contributors.

Skills

PID control

LQR

MPC

Kalman filtering

Python programming

Control system modeling

Written communication

Education

Bachelor's degree in Control Engineering

Master's degree (preferred)

Tools

python-control

SciPy

CasADi

do-mpc

OpenModelica

Modelica/OpenModelica

Julia ControlSystems

Job description

Role Overview

Apply control engineering expertise to help train next-generation AI systems using high-quality, real-world technical input. This remote contract role focuses on designing and deploying robust controllers, modeling complex physical plants, and improving real-world system performance. No prior AI experience is required.

Key Responsibilities

• Design and tune PID and advanced controllers, including LQR, MPC, and Kalman filters, for physical systems such as robotics, drones, automotive platforms, and industrial hardware.
• Develop plant models from first principles and validate them against empirical data using state-space and transfer-function methods.
• Implement and verify control algorithms in Python using open-source tools such as python-control, SciPy, CasADi, do-mpc, Julia ControlSystems, and OpenModelica.
• Analyze system performance, identify improvements, and iterate on designs for optimal real-world operation.
• Document control strategies and engineering decisions clearly, and participate in precise written and verbal technical discussions.
• Collaborate remotely with interdisciplinary contributors while working with technical independence.

Qualifications

• Bachelor’s degree or higher in Control, Electrical, Mechanical, Mechatronics, or Aerospace Engineering.
• More than 5 years of hands-on controller-design experience after completing your degree, including deployment on real systems rather than simulation-only work.
• Experience designing PID controllers, building physical plant models, and validating models through first-principles and data-driven approaches.
• Demonstrated delivery of PID control and at least one modern method, LQR, MPC, or Kalman filtering, on real hardware.
• Python proficiency for control-code development, debugging, and validation with open-source toolchains.
• Exceptional written and verbal English communication skills with an emphasis on clarity and precision.
• Additional valued experience includes a Master’s or PhD, production MPC using do-mpc or CasADi, Modelica or OpenModelica, Julia, system identification, embedded C/C++, ROS, nonlinear, robust, or adaptive control, and publication or open-source contributions.

Work Terms

Remote contract engagement.

Compensation

$30 to $50 per hour.