Control Engineer
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Jul 17, 2026. Venti Technology scores C on the Alion truth index.
A world empowered by autonomy. We build robotic vehicles to improve logistics safety, forge a greener Earth, and enhance human lives.
We are a closely-knit team aspiring to change the world through disruptive technology. We are innovators. We are tinkerers. We are problem-solvers. And we have a fair amount of magic dust up our sleeves. We have a plan for fleet-level deployment of autonomous vehicles, and we are looking for the best-of-the-best to join us in making this a reality.
About Venti Technologies
Based in the U.S. and Asia, Venti Technologies is the leader in safe-speed autonomous logistics systems, developing the future of goods transportation. Using rigorous mathematics, deep learning, and theoretically-grounded algorithms, Venti has a proprietary collection of autonomy technologies including a suite of powerful logistics algorithms. Venti’s proven value proposition of saving costs, increasing vehicle utilization, and improving safety is recognized by customers and driving growth. Launched in 2018, Venti brings together an unsurpassed team internationally. The company has autonomous systems deployed in Asia for industrial and logistics sites and a growing pipeline. Venti has offices in Cambridge (Massachusetts, USA), Suzhou (China), and Singapore - our Asian headquarters.
About the Role
We are looking for a Control Engineer to help develop and improve the motion control system for autonomous trucks. You will work on vehicle control algorithms that enable safe, stable, and reliable autonomous driving in real-world environments. This role involves developing controllers, evaluating vehicle behavior, analyzing test data, and collaborating with cross-functional teams to continuously improve system performance.
Role responsibilities
Research and evaluate modern control methods applicable to autonomous driving and vehicle automation.
Contribute to design, develop, and maintain software for vehicle motion control, including steering and speed control.
Build mathematical models of vehicle behavior by characterizing steering, braking, throttle, actuator response, and system delays.
Improve controller performance through testing, tuning, and calibration across different vehicle platforms and operating conditions.
Collect and analyze vehicle test data to diagnose issues, validate controller behavior, and identify improvement opportunities.
Design and maintain safety features within the control system, including fault detection, command validation, timeout monitoring, and safe recovery strategies.
Improve the resilience of the control software against communication delays, timing variations, missing sensor data, and actuator faults.
Required experience
Bachelor's or Master's degree in Robotics, Control Engineering, Computer Science, Mechanical Engineering, Electrical Engineering, or a related discipline.
Around 1 year of experience in robotics, control systems, autonomous vehicles, or a similar technical field through industry, research, internships, or academic projects.
Understanding of feedback control principles, vehicle dynamics, and controller evaluation.
Experience with system modeling, system identification, or dynamic system analysis.
Familiarity with electromechanical, hydraulic, or pneumatic actuation systems.
Proficiency in modern C++ development on Linux.
Strong analytical thinking, troubleshooting ability, and willingness to learn new technologies.
Bonus experience
Experience with ROS or ROS 2.
Experience integrating software with drive-by-wire or embedded vehicle control systems.
Hands-on experience deploying robotic or autonomous systems outside of simulation.
Knowledge of functional safety practices, risk analysis, or control-related failure analysis.
Familiarity with advanced control techniques such as Model Predictive Control (MPC), gain scheduling, state estimation, Kalman filtering, nonlinear control, or geometric control.
Experience using simulation environments for robotics or autonomous vehicle development.
Understanding of the overall autonomous driving software stack and how control interacts with perception, localization, and planning.