Senior Perception & Real-Time Robotics Lead

Devyantram; Ashburn (GA); On-site; USD 150,000 - 230,000; Full time

Job summary

Devyantram seeks a senior Robotics/Controls engineer to design real-time sensing-to-action layers for advanced bionic and multi-robot systems. You will bridge perception, planning, control, and learning, with a focus on stable, precise, adaptive behavior in real-time loops.

Lead end-to-end ROS2 stack, sensor fusion, and multi-robot coordination; combine unconventional cognitive substrates with traditional control to deliver robust autonomous performance in simulation and on hardware.

Qualifications

• MS or PhD in Robotics, Controls, EE, CS or related field.
• 8+ years in robotics, controls, or real-time autonomy with deployment on physical systems.
• Strong foundation in control theory, robot dynamics/kinematics, and real-time systems.
• Excellent Python and C++ skills.
• Deep ROS2 experience.

Responsibilities

• Architect end-to-end perception to control pipelines.
• Lead sensor fusion across vision, depth, tactile, and proprioceptive modalities.
• Develop closed-loop control for manipulation, locomotion, and balance.
• Apply learning-based and classical control methods (MPC, whole-body control, RL hybrids).
• Own the ROS2-based control stack and simulation-to-real transfer.
• Integrate outputs from cognitive compute layer into deterministic real-time control loops.
• Design multi-robot and swarm coordination: distributed estimation, multi-agent planning, consensus, and formation behaviors.
• Drive performance benchmarking in simulation and on hardware.
• Generate core controls and autonomy IP in coordination with patent counsel.

Skills

Python

C++

ROS2

Control theory

Real-time systems

Robotics

Python programming

Education

MS or PhD in Robotics/Controls/EE/CS

Tools

Isaac Sim

MuJoCo

Gazebo

MPC

Whole-body control

Job description

Devyantram seeks a senior Robotics/Controls engineer to design real-time sensing-to-action layers for advanced bionic and multi-robot systems. You will bridge perception, planning, control, and learning, with a focus on stable, precise, adaptive behavior in real-time loops.

Lead end-to-end ROS2 stack, sensor fusion, and multi-robot coordination; combine unconventional cognitive substrates with traditional control to deliver robust autonomous performance in simulation and on hardware.