Research Intern – Data Engine & Deployment - Teleoperation Systems, Data Pipelines, On-Robot Systems (MS/PhD, 6–12 months)

Proception Inc.; Mountain View (CA); Hybrid; USD 28,000 - 42,000; Part time

Benefits offered by this job

Access to real robot hardware

Mentorship from researchers/engineers

Competitive compensation

Job summary

Proception Inc. is seeking a paid internship in robotics to contribute to the data engine behind robot policies. You will work end-to-end on the teleoperation, data collection, and curation pipeline, collaborating with AI, hardware, and perception teams.

You will own a scoped project and gain hands-on experience with real hardware and large-scale robot datasets. The role emphasizes building practical, working systems and advancing robot learning ideas in a fast-moving environment.

Qualifications

• Pursuing MS/PhD in robotics, CS, EE or related field.
• Strong Python in Linux; C++ a plus, clean, debug-friendly code.
• Hands-on robotics experience via research, projects or internships.
• Familiarity with robot data workflows: demonstrations, logging, data organization.
• Comfort with sensor data (RGB/depth, proprioception, tactile, force-torque).
• Self-directed and rigorous problem solving with timely results.
• Experience with ROS 2 or comparable middleware.
• Experience deploying policies on real hardware.
• Familiarity with robot learning concepts and manipulation setups.

Responsibilities

• Build and improve teleoperation and demonstration-collection components.
• Support data collection operations on real robots to raise throughput and quality.
• Contribute to the pipeline from robot to training set (ingestion, time sync, curation).
• Develop QA, metrics, and visualization tools to keep datasets trustworthy.
• Assist with deploying trained policies on hardware and run on-robot evaluations.
• Assist hardware and sensor bring-up on rigs (cameras, tactile, force-torque).
• Collaborate with AI, hardware, perception teams and own a scoped project from idea to demonstration.

Skills

Python programming

Linux environments

Hands-on robotics

Data workflow

Multimodal sensor data

Debug across stack

ROS 2 or middleware

Real-time systems

Dexterous hands experience

Take initiative

Education

MS or PhD in Robotics/CS/EE

Tools

ROS 2

Real-time systems

Job description

Join our team to help build the data engine behind general-purpose robot policies. You'll work on the pipeline from teleoperated demonstration collection through curation and quality control to on-robot deployment — the systems that turn robot time into training data, and trained policies into robots that work in the real world. You'll own a concrete piece of this stack end to end, working directly with our engineering and research team on real hardware. We care more about your ability to build things that work on real robots than about any particular robot, task, or sensor you've used before.

Requirements

• 01 Currently pursuing an MS or PhD in Robotics, Computer Science, Electrical Engineering, or related field
• 02 Strong software engineering skills in Python (C++ a plus) in Linux environments: you write clean, working code and can debug across the stack
• 03 Hands-on experience with real robots or physical systems — through research, projects, competitions, or prior internships
• 04 Familiarity with the robot data workflow: collecting demonstrations (teleoperation or kinesthetic), logging multimodal sensor streams, and organizing data for training
• 05 Comfortable working with sensor data (RGB/depth cameras, proprioception, tactile, force-torque) — capture, synchronization, and visualization
• 06 Rigorous and self-directed: you can take a loosely specified problem, break it down, and drive it to a working result in a limited time
• 07 (+) Experience with ROS 2 or comparable robotics middleware, or real-time systems
• 08 (+) Experience deploying or evaluating learned policies on real hardware
• 09 (+) Familiarity with robot learning (imitation learning, vision-language-action models) — enough to understand what models need from data
• 10 (+) Experience with dexterous hands, tactile sensing, or contact-rich manipulation setups

Details & responsibilities

• 01 Build and improve components of the teleoperation and demonstration-collection stack — rigs, operator interfaces, and collection workflows
• 02 Support data collection operations on real robots and help raise throughput and data quality
• 03 Contribute to the pipeline from robot to training set: ingestion, time synchronization of multimodal sensor streams, curation, filtering, and annotation tooling
• 04 Build QA, metrics, and visualization tooling that keeps datasets consistent and trustworthy
• 05 Help deploy trained policies to real hardware and run on-robot evaluations
• 06 Assist with hardware and sensor bring-up — cameras, tactile, force-torque — on collection and deployment rigs
• 07 Work directly with the AI, hardware, and perception teams, and own a scoped project from idea to a working, demonstrated result
• 01 Paid internship with competitive compensation
• 02 Work on cutting-edge problems in robot learning and manipulation
• 03 Mentorship from researchers and engineers working at the frontier of embodied intelligence
• 04 Access to real robot hardware and large-scale robot datasets
• 05 Opportunity to publish or contribute to high-impact research alongside product-driven development

Interested in this role?