Robotics Engineer — Real-Time Manipulation & Control

Path Robotics Inc.; Columbus (OH); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Free lunch

Flexible PTO

Medical/Dental/Vision

Parental leave (12-14 weeks)

401(k) plan

Referral bonuses

Job summary

Path Robotics Inc. in Columbus, Ohio, seeks an Algorithms Engineer focused on manipulation and control to own the real‑time closed‑loop from sensing to motion on physical robots. You will lead state estimation, Kalman/particle filtering, and robust control in C++ on real hardware.

Join a team building high‑accuracy, real‑time manipulation with perception‑to‑control integration, deterministic timing, and learning‑based control directions for future scalability.

Qualifications

• Deep, first‑principles real‑time control and state estimation in robotics.
• Manipulation robotics: arm kinematics, dynamics, and trajectory correction.
• Sensor-guided motion and perception–to–control loops on real hardware.

Responsibilities

• Own the real‑time closed loop from sensing to motion, including state estimation, feedback and predictive control.
• Decide what can be estimated from sensing and design fail‑safe systems with quantified uncertainty.
• Develop robust hard‑real‑time software that runs on physical robots (not just sim).
• Shape technical direction toward learning‑based and whole‑body control.

Skills

Real-time control

State estimation

Kalman estimation

Particle filters

Moving-horizon estimation

C++ (real-time)

ROS / ROS 2

Hard real-time software

Trajectory generation

End-effector control

Visual servoing

Uncertainty handling

Tools

ROS/ROS 2

Job description

Path Robotics Inc. in Columbus, Ohio, seeks an Algorithms Engineer focused on manipulation and control to own the real‑time closed‑loop from sensing to motion on physical robots. You will lead state estimation, Kalman/particle filtering, and robust control in C++ on real hardware.

Join a team building high‑accuracy, real‑time manipulation with perception‑to‑control integration, deterministic timing, and learning‑based control directions for future scalability.