Senior Robotics SWE, System Identification & Modeling

Nimble Robotics•San Francisco, CA

6d•$190,000 - $250,000

About The Position

We are looking for a Senior Robotics Software Engineer specializing in System Identification and Modeling to build the core software powering our next-generation autonomous robots. In this role, you will develop and maintain the mathematical models, parameter estimation pipelines, and feedforward/feedback control systems that allow our robots to operate with exceptional reliability, precision, and efficiency in real production environments. You will work across the full robotics and autonomy stack — building robust, production-grade software that scales as we deploy more robots into high-throughput operations — while serving as the team's deep expert in system identification, dynamics modeling, and model-based control. You'll collaborate closely with AI, hardware, controls, and infrastructure teams to integrate frontier AI capabilities with rigorous physics-based models, continually improving robot uptime, performance, and overall intelligence.

Requirements

Bachelor's, Master's, or PhD in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
5+ years of software engineering experience building production robotics systems.
Strong foundation in dynamics, controls, and system identification — including least-squares regression, parameter estimation, state-space and transfer-function modeling, and feedforward/feedback controller design.
Hands-on experience characterizing real electromechanical systems: motors, gearboxes, linear actuators, articulated arms, or similar mechanisms.
Strong proficiency in at least one of the following: Rust, Python, C++.
Proven ability to design, implement, and maintain complex, high-reliability software systems.
Experience integrating software with sensors, actuators, and embedded systems.
Familiarity with software best practices including testing, documentation, code reviews, and robust architectural design.
Excellent communication skills and ability to collaborate across multi-disciplinary teams.
Willingness to support production operations through an on-call rotation.

Nice To Haves

Graduate-level coursework or research in system identification, optimal estimation, or adaptive control.
Experience with nonlinear system identification techniques (e.g., extended Kalman filters, particle filters, neural-network-based model learning).
Familiarity with physics simulators (MuJoCo, Drake, Isaac Sim) and sim-to-real transfer, including using identified parameters to calibrate simulation environments.
Experience with real-time embedded system development, RTOS, or bare-metal firmware.
Exposure to automation environments such as warehousing, manufacturing, or logistics.
Experience with safety-critical systems.
Familiarity with ROS/ROS 2 and standard robotics middleware.
Experience building data pipelines for collecting, storing, and analyzing robot telemetry at scale.

Responsibilities

Design and execute system identification experiments for actuators, mechanisms, and full robot subsystems — motors, arms, elevators, drivetrains — fitting dynamic models via regression and curve-fitting to derive accurate feedforward and feedback controllers.
Own kinematic calibration workflows: DH parameter identification, wheel radius estimation, and tool-center-point calibration to drive measurable improvements in arm accuracy and mobile base odometry.
Build automated calibration and sys-id tooling that runs on production hardware, enabling rapid re-characterization after mechanical changes, wear, or new platform deployments.
Lead design and implementation of robot behaviors and task-level intelligence across the full stack, integrating perception, planning, and control into reliable end-to-end execution across nominal and edge-case scenarios.
Drive measurable improvements in autonomy quality and arm accuracy using data, operational metrics, and model validation (diagnostic plots, residual analysis, statistical benchmarks).
Collaborate with hardware engineering on software–hardware integration for new platforms and upgrades; triage and resolve production robotics issues.
Lead technical design reviews, drive architecture decisions for core subsystems, and mentor engineers and technicians on reliability, testing, and operational excellence.