About Nimble
Nimble is an AI robotics company building the autonomous supply chain to power fast, efficient and economical commerce. We're training robot AGI to power a proprietary generalist supply chain superhumanoid, the first robot in the world capable of performing thousands of tasks across the supply chain. We've raised over $220M at over $1B valuation and formed a strategic alliance with FedEx to build a national network of autonomous warehouses capable of generating many billions in annual revenue. We are a hardcore and obsessed team of the world's best engineers and operators. If you are obsessed with your craft, enjoy a high-intensity and fast moving high impact environment, are super high agency in getting hard things done and want to be part of building the world's most legendary robotics company at the most pivotal moment in history, we want to work with you.We are on a mission to empower and inspire mankind to accomplish legendary feats by inventing robots that liberate us from the menial. We will accomplish this by training robot AGI to invent and build the Autonomous Supply Chain – everything from the inside of factories and warehouses to your front door – powered by generalist superhumanoids.Our founding team comes from the AI labs at Stanford and Carnegie Mellon and our board of directors include famed robotics and AI legends including Fei-Fei Li (Chief Scientist of AI at Google and Director of Stanford's AI Lab), Marc Raibert (founder of Boston Dynamics), and Sebastian Thrun (founder of GoogleX, Waymo; Stanford Professor and considered the father of autonomous vehicles).Let's be legendary.
Link: Nimble Closes $106 Million Series C Funding Round, Scales Fully Autonomous Fulfillment with FedEx
Link: FedEx Announces Expansion of FedEx Fulfillment With Nimble Alliance
Why Join Nimble?
At Nimble, we are committed to building legendary products, a legendary team, and a legendary legacy. Join us and become part of an ambitious, humble, and resourceful culture where your work will leave a lasting impact on the future of robotics and commerce.
Nimble's Core Values:
Be relentlessly resourceful - Challenge conventions and overcome obstacles.
Be legendary - Be the very best and do work that inspires.
Be humble - Prioritize growth, learning, and doing whatever is needed to further the mission.
Be dependable - Take ownership and deliver with high agency.
About the RoleWe 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.
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 benchm