Robotics Controls Engineer, Teleo

• The ideal candidate will have extensive experience in robotics, control systems, and system identification, coupled with a strong interest in real-world validation and a passion for developing scalable automation software solutions
• Pursuing/completed Ph.D. or Master’s degree in Control Engineering, Robotics, Computer Science, or a related field. Exceptional Bachelor’s degree candidates with relevant experience may also be considered
• Strong proficiency in Python or MATLAB
• Solid understanding of system identification and parameter estimation

Desirable

• At Teleo, we work with a variety of heavy machinery—dozers, trucks, wheel loaders, bobcats, and more—across multiple brands and sizes
• Achieving precise automatic control, whether through LQR, MPC, or reinforcement learning, requires accurate mathematical models of these machines. However, detailed models that fully capture hydraulics and ground interactions can be excessively complex. Our goal is to strike the right balance between model fidelity and complexity
• Fully embedded within Teleo’s autonomy team, this internship will focus on building a complete suite of tools and algorithms to determine the optimal parameter set that allows a simulated model to best replicate real-world machine behavior
• With access to a wide range of vehicles at Teleo’s proving ground facility, you will have the opportunity to validate simulations against real-world machine responses
• Design control inputs to efficiently expose key machine parameters while respecting test area constraints
• Automate data collection for model identification
• Develop algorithms to estimate optimal machine parameters based on observed system responses
• Evaluate model performance by comparing simulated vs. real-world machine responses