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AI / ML · AI

Robotics Engineer/Researcher - Data Engine & Deployment - Teleoperation Systems, Data Pipelines, On-Robot Systems

Proception Inc

On-siteFull-timeListed 1mo ago
Apply now

Backed by

Y Combinator

HQ

🇺🇸 San Francisco

Open roles

70

How to stand out for Robotics Engineer/Researcher - Data Engine & Deployment - Teleoperation Systems, Data Pipelines, On-Robot Systems at Proception Inc

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About the role

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All open rolesAI⭐ Robotics Engineer/Researcher - Data Engine & Deployment - Teleoperation Systems, Data Pipelines, On-Robot SystemsMountain View, CA (On-Site)/Full-timeApply nowShareAbout the roleJoin our team to build the data engine behind general-purpose robot policies. You'll own the pipeline from teleoperated…

What you will do

  • Design and build the teleoperation and demonstration-collection stack — rigs, operator interfaces, and workflows that maximize throughput and data quality
  • Run data collection operations end to end: task and protocol design, operator onboarding, and day-to-day collection on real robots
  • Build the pipeline from robot to training set: ingestion, time synchronization of multimodal sensor streams, storage and dataset formats, curation, filtering, and annotation tooling
  • Develop the QA, metrics, and visualization tooling that keeps datasets consistent, well-covered, and trustworthy
  • Deploy trained policies to real hardware: real-time inference, latency optimization, safety monitors, and graceful failure handling

What they are looking for

  • BS, MS, or PhD in Robotics, Computer Science, Electrical Engineering, or related field — or equivalent experience
  • Strong software engineering skills in Python and C++ in Linux environments: you write robust, maintainable systems code that runs on real hardware
  • Hands-on robotics experience: hardware bring-up, sensor and actuator integration, calibration, and debugging full-stack issues on physical systems
  • Experience building teleoperation and demonstration-collection systems — rigs, operator interfaces, and workflows — and scaling collection throughput and operator efficiency
  • Experience building data pipelines for multimodal robot data: ingestion, time synchronization across sensors, storage and dataset formats, curation, filtering, and annotation tooling
  • Experience deploying learned policies on real robots: real-time inference, latency and throughput optimization, safety monitors, and graceful failure handling
  • Comfortable working with multimodal sensor streams (RGB/depth cameras, proprioception, tactile, force-torque) — drivers, logging, and synchronized capture
  • Rigorous about data quality: metrics and visualization for dataset coverage and consistency, automated QA, and regression testing of the collection-to-deployment loop
  • (+) Experience with ROS 2 or comparable robotics middleware, real-time systems, and containerized deployment across a fleet of robots
  • (+) Familiarity with robot learning workflows (imitation learning, vision-language-action models) — enough to shape data collection around what models actually need
  • (+) Experience with dexterous hands, tactile sensing, or contact-rich manipulation setups

Benefits

  • Competitive salary and meaningful equity
  • Full health, dental, and vision insurance
  • Access to custom-built dexterous robots
  • Collaboration with leading researchers in robotics and AI
  • High-ownership role with the opportunity to lead core initiatives in real-world robot learning
RoboticsSoftware engineeringHardware bring-upSensor and actuator integrationTeleoperationData pipelinesReal-time inferenceData qualityPythonC++LinuxROS 2
Full posting text

All open rolesAI⭐ Robotics Engineer/Researcher - Data Engine & Deployment - Teleoperation Systems, Data Pipelines, On-Robot SystemsMountain View, CA (On-Site)/Full-timeApply nowShareAbout the roleJoin our team to build the data engine behind general-purpose robot policies. You'll own 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.

We care more about your ability to build reliable, high-throughput systems around real robots than about any particular robot, task, or sensor you've used before.Requirements01BS, MS, or PhD in Robotics, Computer Science, Electrical Engineering, or related field — or equivalent experience02Strong software engineering skills in Python and C++ in Linux environments: you write robust, maintainable systems code that runs on real hardware03Hands-on robotics experience: hardware bring-up, sensor and actuator integration, calibration, and debugging full-stack issues on physical systems04Experience building teleoperation and demonstration-collection systems — rigs, operator interfaces, and workflows — and scaling collection throughput and operator efficiency05Experience building data pipelines for multimodal robot data: ingestion, time synchronization across sensors, storage and dataset formats, curation, filtering, and annotation tooling06Experience deploying learned policies on real robots: real-time inference, latency and throughput optimization, safety monitors, and graceful failure handling07Comfortable working with multimodal sensor streams (RGB/depth cameras, proprioception, tactile, force-torque) — drivers, logging, and synchronized capture08Rigorous about data quality: metrics and visualization for dataset coverage and consistency, automated QA, and regression testing of the collection-to-deployment loop09(+) Experience with ROS 2 or comparable robotics middleware, real-time systems, and containerized deployment across a fleet of robots10(+) Familiarity with robot learning workflows (imitation learning, vision-language-action models) — enough to shape data collection around what models actually need11(+) Experience with dexterous hands, tactile sensing, or contact-rich manipulation setupsDetails & responsibilities01Design and build the teleoperation and demonstration-collection stack — rigs, operator interfaces, and workflows that maximize throughput and data quality02Run data collection operations end to end: task and protocol design, operator onboarding, and day-to-day collection on real robots03Build the pipeline from robot to training set: ingestion, time synchronization of multimodal sensor streams, storage and dataset formats, curation, filtering, and annotation tooling04Develop the QA, metrics, and visualization tooling that keeps datasets consistent, well-covered, and trustworthy05Deploy trained policies to real hardware: real-time inference, latency optimization, safety monitors, and graceful failure handling06Bring up and integrate sensors and hardware — cameras, tactile, force-torque — across collection and deployment rigs07Collaborate across AI, hardware, and perception teams to close the loop from deployment results back into data collectioCompensation & benefits01Competitive salary and meaningful equity02Full health, dental, and vision insurance03Access to custom-built dexterous robots04Collaboration with leading researchers in robotics and AI05Backed by YC and top-tier investors06High-ownership role with the opportunity to lead core initiatives in real-world robot learningInterested in this role?

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Proception Inc

Industrials

Making humanoids dexterous enough to thread a needle

Backed by Y Combinator

Company pageWebsite

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