We are hiring a Masters- or PhD-level Research Engineer with hands-on experience building software for human-in-the-loop teleoperation systems. This role focuses on closing the embodiment gap between models trained in simulation or video and reliable real-world robotic behavior. This is a founding-level senior position.

Teleoperation System Architecture

• Build and maintain software for HITL robotic control

• Connect operator interfaces, robots, and learning pipelines

• Implement shared-control, arbitration, and autonomy handoff logic

• Improve supervision scalability and operator-to-robot ratios

Probabilistic Robotics & Modeling

• Develop systems grounded in Bayesian inference and uncertainty-aware control

• Integrate teleoperation data into probabilistic world models

• Design feedback signals that improve belief updates and policy learning

• Build systems robust to partial observability and model uncertainty

Simulation, Video Learning & Embodiment Transfer

• Identify where simulation- or video-trained models break on real hardware

• Design methods that explicitly reduce embodiment mismatch

• Convert simulated or observational training into stable, deployable robot policies through improved world models, data pipelines, and control integration

Real-Time Robotics Infrastructure

• Work on low-latency networking, streaming, and control pipelines

• Integrate perception, planning, and control stacks

• Contribute to fleet monitoring, observability, and deployment tooling

• Support simulation-to-real validation workflows

Need to have:

• Masters or PhD in Robotics, Computer Science, Electrical Engineering, or similar

• Experience building teleoperation, shared autonomy, or HITL robotics systems

• Strong programming ability (Python, C++, or similar)

• Demonstrated expertise in probabilistic modeling, state estimation, or Bayesian inference

• Experience deploying software on real robotic systems

Nice to have:

• Robotics autonomy or control stacks

• Systems converting human interaction into training signals

• Modern simulation or world-model training platforms

• Sim-to-real transfer and embodiment-gap mitigation techniques

Compensation includes salary anchored in the cited range + equity in Noumenal Labs.

Noumenal Labs is an equal opportunity employer. We do not discriminate on the basis of age, disability, sex, race, religion or belief, gender, marriage/civil partnership, pregnancy/maternity, or sexual orientation.