Process control engineer serp_jobs.h1.location_city

Position Overview

Dexmate is at the forefront of developing advanced robotic systems that solve real-world challenges. We're building next-generation robots designed to work alongside humans, operate in human environments, and help address growing labor shortages.

Key Responsibilities

Develop and implement state estimation, sensor fusion, planning, control algorithms that enable fast, dynamic and safe robot motion

Collaborate with cross-functional teams including embedded system, perception, hardware, AI

Optimize control performance across multiple domains including stability, safety, precision, and energy efficiency

Design and conduct experiments to validate control algorithms both in simulation and on hardware

Analyze system performance data to identify failure modes and improvement opportunities

Document technical approaches, implementation details, and experimental results

Requirements

Master's or PhD in Robotics, Controls, Mechanical Engineering, or related technical field

4+ years of professional experience developing control systems for dynamic robots

Strong expertise in control theory including nonlinear control, model predictive control, and optimal control

Experience with state estimation techniques such as Kalman filters, particle filters, and factor graphs

Proficiency in C++, Python, Rust for real-time robotics applications

Strong understanding of robot kinematics, dynamics, and mathematical modeling

Experience working with sensor integration including IMUs, encoders, force / torque sensors

Proven track record of implementing and testing control algorithms on physical robotic systems

Excellent problem-solving skills and ability to debug complex system interactions

Preferred Qualifications

Experience with highly dynamic control systems such as bipedal, quadruped, or humanoid robots

Knowledge of reinforcement learning or other machine learning approaches for control

Experience with whole-body control and contact dynamics for legged systems

Experience with real-time computing and optimization

Background in trajectory optimization and motion planning

Familiarity with ROS, simulation environments (e.g., Drake, Isaac Sim, SAPIEN, MuJoCo, PyBullet)

Track record of publications in top-tier robotics conferences / journals