System Identification & Controls Engineer

Menlo Ventures; San Mateo (CA); On-site; USD 90,000 - 130,000; Full time

Job summary

Menlo Ventures is seeking a System Identification & Controls Engineer to model and validate robotics dynamics for various applications. This role requires a candidate with a robust background in system identification on real robots and a deep understanding of classical control principles.

The ideal applicant will have experience designing tests and leading automation efforts across robotics platforms. Passionate individuals eager to pioneer advancements in robotic technology are encouraged to apply.

Qualifications

• Demonstrated hands-on track record of system identification on physical robotic systems.
• Strong foundation in classical controls and feedback/feedforward systems.
• Practical experience in excitation design and parameter estimation.

Responsibilities

• Plan and run system identification across Skild robot platforms.
• Design excitation trajectories and know the purpose of experiments.
• Characterize actuators and motors with diverse teams.
• Build automated pipelines for system identification.

Skills

System identification

Classical controls

Python

C++

Hardware data collection

Education

MS or PhD in Mechanical/Electrical Engineering, Controls, Robotics, Aerospace

Tools

MATLAB/Simulink

MuJoCo

ROS/ROS2

Job description

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.