Robotics Controls Engineer - Internship

Job Description

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Teleo is a robotics startup disrupting a trillion-dollar industry. Teleo converts construction heavy equipment, like loaders, dozers, excavators, trucks, etc. into autonomous robots. This technology allows a single operator to efficiently control multiple machines simultaneously, delivering substantial benefits to our customers while significantly enhancing operator safety and comfort.

Teleo is founded by Vinay Shet and Rom Clément, experienced technology executives who led the development of Lyft’s Self Driving Car and Google Street View. Teleo is backed by YCombinator, Up Partners, F-Prime Capital, and a host of industry luminaries. Teleo’s product is already deployed on several continents and generating revenue.

Teleo is poised for rapid growth. This presents a unique opportunity to be part of a team that is creating a product with a profound impact on our customers, working on cutting-edge 100,000-pound autonomous robots, engineering intricate systems at the intersection of hardware, software, and AI, and joining the early stages of an exciting startup journey.

About the Role

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.

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.

Note: Candidates must have their own transportation to access Teleo’s testing facility, as public transit may not be available.

Responsibilities

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.

Minimum Qualifications

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.

Preferred Qualifications

Proficiency in C++, Python, and MATLAB.

Familiarity with nonlinear optimization software (such as Acados, Drake, or CasADi).

Extensive experience in system identification for automatic control, ideally across LQR, MPC, and RL-based approaches.

Experience with software version control systems (Git or equivalent).

Self-motivated and capable of independently planning and executing tasks.

This internship is a unique opportunity to work on real-world control challenges in autonomous heavy machinery. If you're passionate about system modeling, control theory, and data-driven optimization, we’d love to hear from you!

Teleo is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. All qualified people are encouraged to apply.

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