Join Skild AI as a System Identification & Controls Engineer to model and validate robotic dynamics at fleet scale.
Posted by employer 3 months ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
Skills & Technologies
Requirements
- Experience
- 5+ years
- Education
- Master's degree
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
The System Identification & Controls Engineer at Skild AI focuses on characterizing and validating the dynamics of robotic systems, ensuring accurate performance across various platforms. This role requires expertise in system identification, classical controls, and hands-on experience with robotic hardware, particularly in real-world applications. Ideal candidates are seasoned professionals with a strong background in mechanical or electrical engineering and a proven track record in robotics. Skild AI fosters a collaborative environment where innovative problem-solving is key to advancing their cutting-edge robotic intelligence.
Joblaze insights
- Listed 9 days ago on Joblaze — tracked directly from Skild AI's career page.
- Skild AI has 63 other open roles including Manufacturing Engineering Manager, Senior Electrical Engineer , Operations Program Manager – Data Infrastructure - India.
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Quick facts
- How much experience is required?
- At least 5 years of relevant experience for this System Identification & Controls Engineer role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: C++, Drake, Isaac Sim, Linux, MATLAB, MuJoCo.
- What seniority level is this role?
- Skild AI targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this System Identification & Controls Engineer role at Skild AI.
From the original posting
Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We're hiring a System Identification & Controls Engineer to characterize, model, and validate the dynamics of every robot we work with — as accurately as possible, and at fleet scale. This is a senior individual-contributor role for someone who has done rigorous system identification on real robots before and walks in already knowing which tests to run.
Responsibilities
- Plan and run system identification across all Skild robot platforms — actuators, transmissions, joints, rigid-body dynamics, and sensors.
- Design the excitation trajectories and bench/on-robot tests, and know which experiment answers which question.
- Characterize actuators and motors on dynamometers, test benches, and hardware-in-the-loop setups, alongside the EE, ME, and firmware teams.
- Fit dynamics models, quantify their accuracy, and close the sim-to-real gap against our simulators.
- Apply classical controls — state estimation, calibration, stability and bandwidth analysis — to real hardware.
- Build automated pipelines that scale identification from a single robot to the whole fleet.
- Quantify unit-to-unit variation, track drift and wear over time, and flag outlier units.
- Set the standard and tooling for system identification at Skild, and document findings rigorously.
Preferred Qualifications
- MS or PhD in Mechanical/Electrical Engineering, Controls, Robotics, Aerospace, or a related field — or equivalent hands-on experience.
- A demonstrated, hands-on track record of system identification on real robotic or electromechanical hardware — identified and validated on physical systems, not just in simulation.
- Strong classical controls foundation: feedback/feedforward and cascade control, frequency-response and stability analysis, state estimation and Kalman filtering.
- Solid grasp of robot hardware and mechatronics: motors and field-oriented control, transmissions, encoders, IMUs, and force-torque sensors.
- Practical experience with excitation design, hardware data collection, and parameter estimation (time- and frequency-domain methods).
- Proficiency in Python and C++ in a Linux environment; MATLAB/Simulink a plus.
- Familiarity with robotics dynamics tooling and simulators (MuJoCo, Isaac Sim, Drake, Pinocchio, ROS/ROS2).
- Experience deploying calibration or controls across a large fleet of robots or vehicles is highly valued.