Why this role stands out
This role offers a significant opportunity to shape the future of AI robotics, contributing to groundbreaking advancements in autonomous supply chains with a highly reputable company. You'll thrive here if you are a driven, mid-senior SWE passionate about system identification and modeling, eager to make a substantial impact on a world-changing mission. With a competitive salary of $190,000, this is an exciting chance to join a legendary team and push the boundaries of what's possible.
Quick overview
Job description
About the Role
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.
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.
Qualifications
- 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 Have
- 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.
Compensation & Benefits
The pay range for this position at the start of employment is expected to be between $190,000 and $250,000/year. Your exact offer may vary depending on multiple individualized factors, including job-related knowledge, skills, and experience. In addition to cash compensation, this position will also receive generous equity for this position.Similar jobs
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