Farooq77Farooq77
HomeAboutServicesAgencyFeatured WorksTestimonialsJobsArticlesContact
F77

Farooq77

AI Automation Engineer & Agency Lead

Building intelligent automation systems with Python, AI agents, APIs, and workflow automation that help businesses save time, reduce costs, and scale efficiently.

Company

HomeAboutAgencyContactFAQ

Expertise

ServicesProcessTech StackFeatured Work

Resources

JobsArticles

Connect

EmailLinkedInGitHub

Currently Available

Open for Projects & Vendor Partnerships

Start a Project →
Privacy PolicyTerms of ServiceCookie PolicyDisclaimer

© 2026 Farooq77. All rights reserved.

Designed & Developed by Muhammad Farooq

CONTRACTOR•Remote•Active

Control System Engineer

Contribute advanced control engineering expertise to a customer project focused on real-world control solutions and AI training. Design and tune controllers, develop and validate plant models, implement control algorithms in Python, analyze system performance, and provide engineering insights based on real hardware deployment across robotics, drones, automotive, or industrial systems.

Salary

USD30 - USD50 / hour

Department

Control Systems & AI Engineering

Experience

Over 5 years of hands-on controller design experience after completing a relevant engineering degree, with proven deployment of controllers on real physical systems

Curated by Farooq77 Jobs

Role fit snapshot

Engagement
Remote contractor | micro1 application platform
Experience
Minimum recorded experience: Over 5 years of hands-on controller design experience after completing a relevant engineering degree, with proven deployment of controllers on real physical systems
Core expertise
Control Systems & AI Engineering | PID Controller Design | Controller Tuning | Plant Modelling
Named tools
Python
Geographic eligibility
Not specified beyond Remote
Listing dates
Posted 2026-09-23 | Valid through 2026-10-23
Compensation
Recorded compensation: $30-$50/hour

Responsibilities

  • Design and tune PID and advanced controllers such as LQR, MPC, and Kalman Filters for physical systems.
  • Develop plant models from first principles and validate them against empirical data using state-space and transfer function methodologies.
  • Implement and verify control algorithms in Python using open-source control toolkits.
  • Document engineering decisions and control strategies through clear written communication and technical discussions.
  • Analyze system performance, identify improvement opportunities, and iterate on controller designs for real-world operation.
  • Collaborate remotely with interdisciplinary contributors while maintaining technical autonomy and independence.

Skills

PID Controller DesignController TuningPlant ModellingReal System DeploymentLQRMPCKalman FiltersState-Space ModellingTransfer FunctionsPythonpython-controlSciPyCasADido-mpcJulia ControlSystemsOpenModelicaSystem IdentificationControl Algorithm DevelopmentControl ValidationRoboticsDronesAutomotive SystemsIndustrial Control

Requirements

  • Bachelor’s degree or higher in Control, Electrical, Mechanical, Mechatronics, or Aerospace Engineering.
  • Over 5 years of hands-on controller design experience after completing a relevant degree.
  • Proven experience deploying controllers on real physical systems rather than simulation-only projects.
  • Proficiency in building and validating physical plant models using first-principles and data-driven methods.
  • Demonstrated delivery of classical PID control and at least one modern control method such as LQR, MPC, or Kalman filtering on real hardware.
  • Fluency in Python for control code development, debugging, and validation using open-source stacks.
  • Exceptional written and verbal English communication skills with a focus on clarity and precision.
  • Master’s or PhD is a plus.
  • Experience with production MPC using do-mpc or CasADi, Modelica/OpenModelica, Julia, system identification, embedded C/C++, ROS, nonlinear control, robust control, adaptive control, publications, or open-source projects is valued.

Benefits

  • Remote contractor opportunity.
  • Compensation of $30–$50 per hour.
  • Opportunity to contribute real-world control engineering expertise to next-generation AI systems.
  • No prior AI experience required.
  • Opportunity to work on physical-system control problems across robotics, drones, automotive, and industrial applications.

Before you apply

  • Confirm that your location is eligible for the role.
  • Confirm the employment or contract type.
  • Verify the current compensation at the official source.
  • Review the required skills and experience.
  • Check that the listing is still open before applying.
  • Never pay a fee to submit a job application.
This listing is curated by Farooq77 and may originate from a third-party employer or platform. The application link may include referral or tracking parameters. The official application source is the final authority for role details, eligibility, compensation, and availability.
Apply Now →

Related jobs

  • Senior AI Trainer

    CONTRACTOR

  • Contract Attorney

    CONTRACTOR