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Teleoperation Controls Engineer

• Posted 3 hours ago • Updated 3 hours ago

Full Time

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Job Details

Skills

FLSA
Personas
Artificial Intelligence
Bridging
Data Collection
Training
SAFE
NATURAL
Motion Control
Estimating
Algorithms
Interfaces
Retargeting
Mapping
Mechanical Engineering
Electrical Engineering
Computer Science
FOCUS
Classical Mechanics
Dynamics
Modeling
C++
Rust
Python
Real-time
Software Engineering
Testing
Documentation
Assembly
Robotics
RAN
Virtual Reality
ARM
SIM
Sensors
Computer Hardware
HTC Vive
Machine Learning (ML)

Summary

Job Title: Teleoperation Controls Engineer

Department: Sofware Engineering

Employment Type: Full Time

FLSA: Exempt

Location: Houston, TX or Pensacola, FL - Onsite

About the Role

The Persona AI Teleoperation Team bridges operator intents and robot actions. We build immersive interfaces for control to demonstrate the robot's capabilities and data collection to teach the robot new skills for training our industrial foundation models. As a Teleoperation Controls Engineer, you will own the control layer that makes that bridge feel seamless. You will implement and tune the motion control systems that translate operator intent into precise, safe, and natural robot movement. Latency is not just a system constraint to you - it is a human one. You understand that how a robot responds to an operator is the difference between genuine presence and a frustrating disconnect.

What You'll Build

Motion control systems that translate operator commands into smooth, precise robot movement in real time.
Teleoperation control pipelines that apply and tune existing control frameworks -impedance, admittance, and model predictive control - to the specific demands of humanoid operation.
Force estimation algorithms for rendering on teleoperator's interfaces.
Kinodynamic retargeting pipelines that translate human operator motion into robot joint commands with low latency and high fidelity as well as mapping between human and the robot.
Calibration and validation pipelines that ensure control system performance is consistent and measurable across hardware iterations.
Compliant control of the robot in contact.

What We're Looking For

PhD in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science or a related field with focus on controls, dynamics, or manipulation.
Strong foundation in robot kinematics and dynamics including forward and inverse kinematics, Jacobians, and dynamics modeling for articulated bodies.
Hands-on experience implementing and tuning motion controllers on real robot hardware including impedance control, admittance control, or model predictive control in a product context.
Experience working with teleoperation control systems, translating human operator input into robot joint commands with low latency and high fidelity.
Proficiency in C++, Rust or Python for real-time control systems.
Practical understanding of real-time constraints - you know what it means to close a control loop at 1kHz, what breaks when you miss a timing deadline, and typical causes of chatter and other control instabilities.
Strong software engineering fundamentals - clean APIs, systematic testing, clear documentation, and the ability to make complex systems reliable and maintainable.
Background in contact-rich manipulation including grasping, insertion, assembly, or other tasks where force control matters.
Prior work at a robotics company where you shipped a controls system that ran on real hardware in a real environment.
Demonstrated ability to dig into third party libraries, understand them deeply, and contribute back upstream.

Nice to Have

Experience with multiple operator input modalities including motion capture, VR controllers, haptic devices, or exoskeleton systems.
Experience with humanoid robot platforms and familiarity with whole-body control or loco-manipulation for coordinating arm and leg motion simultaneously.
Background in sim-to-real transfer for controls and validating controllers in simulation before deploying to hardware.
Experience with force-torque sensor integration and haptic feedback systems.
Familiarity with modern teleoperation hardware including Gello, Vive Trackers, ALOHA, or similar.
Interest in the intersection of controls and robot learning - understanding how teleoperation data feeds downstream ML pipelines.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 80183771
Position Id: 4edff8e03309475842a427706e3fa4b0
Posted 3 hours ago

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