Some companies are hiring people to teleoperate humanoid robots, capture demonstrations, and label training data. That creates a real but specialized kind of work—not evidence that workers displaced by robots will commonly be rehired to train them. Current job listings show what two employers say these roles involve; they do not establish how many such jobs exist, who gets them, or how many blue-collar jobs humanoids will replace.
What does it mean to train a humanoid robot?
In the current examples, training is practical data work as well as demonstration. A person may guide a robot through a task remotely, record the robot’s activity, annotate or label the resulting data, and flag failures for the AI team. Those steps give developers examples and feedback to use in improving a system; they do not mean that a worker independently programs the robot or guarantees it can perform the task safely without supervision.
Figure’s Humanoid Robot Pilot role
Figure’s job listing describes wearing teleoperation equipment and guiding a robot through designated behaviors. It also assigns the worker responsibility for uploading collected data to an AI training system, reporting issues to the AI team, and following safety and maintenance procedures. The listing calls the position a six-month fixed-term role. That is one company’s stated staffing model, not evidence of a standard job description or stable career path across the industry.
Humanoid’s AI Data Collector role
Humanoid’s listing, published March 23, 2026, describes on-site teleoperation, structured task execution, dataset capture, annotation, and labeling. It also mentions a Universal Manipulator Interface. Together, the two postings illustrate that robot-training work can include both operating equipment and preparing or checking the data that comes out of a task.
Free tools Windows power users keep installed
One-click scans. No signup required.
#1 Best Overall
- 【Humanoid Robot with ESP32】 Powered by ESP32 and 17 intelligent servos, Tonybot smart humanoid robot delivers smooth, dynamic performance. Use the app to easily control it for walking, dancing, kicking, and more. Tonybot can stand up automatically, which is great for playing football and performing gymnastics.
- 【Multimodal Large AI Models】Powered by an AI model module that combines language, voice, and vision models, Tonybot Ultimate Kit unlocks advanced embodied AI functions such as natural conversation and scene understanding. (Ultimate Kit Only)
- 【AI Vision & Voice Interaction】Equipped with an ESP32-S3 vision module and voice interaction module, Tonybot AI robot enables offline face recognition, target tracking, visual line following, voice control, and more. Customize commands and train it to be your AI assistant.
- 【Expandable AI Development with Sensors】 Tonybot robot kit comes with an ultrasonic sensor, IMU sensor, buzzer, and supports modules like dot matrix display, fan, temp/humidity sensors, and WiFi for endless AI-driven development.
- 【3 Programming Options & Comprehensive Tutorials】Tonybot smart AI robot supports Arduino, Python, and Scratch programming, with open-source low-level code and step-by-step tutorials covering everything from beginner learning to advanced humanoid robot development.
| Employer and role | Work described in the listing | Term or other detail stated |
|---|---|---|
| Figure, Humanoid Robot Pilot | Teleoperate the robot through designated behaviors; upload collected data; report issues; follow safety and maintenance procedures. | Six-month fixed-term role. |
| Humanoid, AI Data Collector | On-site teleoperation; structured tasks; dataset capture, annotation, and labeling; use a Universal Manipulator Interface. | Published March 23, 2026; term not stated in the listing summary. |
These examples establish that employers have described paid work connected to humanoid data collection and operation. They do not establish the number of openings, whether either role is ongoing, what share of workers are former tradespeople, or whether the roles require a degree. The listings should be read as employer-specific descriptions, not as a reliable forecast of a new occupation’s scale.
Will the people training robots be the workers whose jobs they replace?
That is possible, but it is not demonstrated by the available examples. Someone with experience in a warehouse, factory, or other physical workplace may understand task sequence, awkward handoffs, and common failure points. That knowledge could be useful when collecting examples or identifying when a robot behaves incorrectly. But neither listing establishes that employers are recruiting displaced workers, prioritizing trade experience, or offering a transition route from an automated job into robot training.
Training a robot also does not automatically protect the trainer’s former job. A company can use workers to gather data while testing whether a machine can later take over some of the same tasks. Whether automation complements staff or substitutes for tasks or headcount depends on the deployment and how the employer reorganizes work. Training roles may be temporary or limited in number even where automation is substantial.
Rank #2
- Al-Driven & Raspberry Pi Powered. TonyPi is a high-performance AI vision robot designed for AI education applications. It is powered by the Raspberry Pi 5, integrated with an OpenCV image processing library and robotic inverse kinematics algorithms. Offering open-source access, TonyPi provides a flexible development environment that supports advanced AI robotics development.
- AI Large Model ChatGPT Integration for Enhanced User-Machine Interaction. TonyPi incorporates a multimodal model, with ChatGPT at the core of its interaction system. With AI vision and voice integration, TonyPi excels in perception, reasoning, and action, enabling advanced embodied AI applications and delivering a seamless, intuitive human-machine interaction experience!
- AI Voice Command & Recognition. Equipped with Large Language Models, TonyPi accurately understands voice commands, analyzes visual scenes in its field of view, and carries out appropriate actions—enabling smooth and responsive voice interaction.
- AI Vision Recognition and Tracking. TonyPi's 2DOF head is fitted with an HD camera that provides a wide field of view. It supports a range of AI vision capabilities, including color recognition, target tracking, ball kicking, line following, and MediaPipe-based motion control for interactive AI applications.
- Comprehensive Learning Resources. TonyPi offers abundant educational content, including resources on robotic motion control, OpenCV, deep learning, MediaPipe, AI large models, voice interaction, and sensor applications. We provide extensive learning materials and tutorials to guide you from foundational concepts to advanced practices, helping you develop your AI humanoid robot.
What do the job forecasts actually say?
The World Economic Forum’s Future of Jobs Report 2025 estimates that macrotrends overall will create 170 million jobs and displace 92 million by 2030, for a net increase of 78 million. In a separate estimate, it associates robotics and autonomous systems with a net decline of 5 million jobs by 2030. These are global estimates based on employer expectations and other data; they are not counts of jobs already lost and do not isolate humanoid robots as the cause.
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →It is also important not to treat every robot statistic as a humanoid statistic. Eurofound reported that in 2022 approximately one in five large companies in the EU used industrial robots and one in ten used service robots. Those adoption figures cover robot categories, not humanoids specifically, and they do not measure how many workers were displaced.
Task change is not the same as a disappearing occupation
Automation can alter the tasks people do, the skills employers seek, and the pace at which workers move between jobs without producing an immediate decline in total employment for an occupation. A 2024 summary by Germany’s IAB of a manufacturing study reported increased churn among low-skilled workers but did not find declining employment for any occupational or age group in its analysis. That finding is specific to the study and should not be generalized to every sector or future humanoid deployment.
Rank #3
- Al-Driven & Raspberry Pi Powered. TonyPi is a high-performance AI vision robot designed for AI education applications. It is powered by the Raspberry Pi 5, integrated with an OpenCV image processing library and robotic inverse kinematics algorithms. Offering open-source access, TonyPi provides a flexible development environment that supports advanced AI robotics development.
- AI Large Model ChatGPT Integration for Enhanced Human-Machine Interaction. TonyPi incorporates a multimodal model, with ChatGPT at the core of its interaction system. With AI vision and voice integration, TonyPi excels in perception, reasoning, and action, enabling advanced embodied AI applications and delivering a seamless, intuitive human-machine interaction experience!
- AI Voice Command & Recognition. Equipped with ChatGPT, TonyPi accurately understands voice commands, analyzes visual scenes in its field of view, and carries out appropriate actions—enabling smooth and responsive voice interaction.
- AI Vision Recognition and Tracking. TonyPi's 2DOF head is fitted with an HD camera that provides a wide field of view. It supports a range of AI vision capabilities, including color recognition, target tracking, ball kicking, line following, and MediaPipe-based motion control for interactive AI applications.
- High-Voltage Intelligent Bus Servos. Equipped with 16 high-voltage intelligent bus servos, TonyPi offers rapid response times and stable output, enabling precise multi-joint coordination and complex motion control. This ensures accurate humanoid postures and interactive movements to meet various demands.
Why is it hard to know how many jobs robots will change?
Employment changes have multiple possible causes: technology, demand, business decisions, and broader economic shifts can occur at the same time. The U.S. Government Accountability Office noted in its 2019 report that U.S. workforce data do not reliably identify whether employment shifts were caused by technology adoption or other forces. The Census Bureau’s experimental data on manufacturing industrial robotic equipment, released in 2025 and covering 2022, tracks robot presence, exposed workers, and investment. It is a step toward measurement, but it remains experimental and does not provide a count of humanoid trainer jobs.
As a result, claims that humanoids will create a particular number of trainer jobs—or eliminate a particular number of blue-collar jobs—go beyond what these sources establish. The distinction matters for workers weighing a career move and for communities estimating how automation may affect local employment.
What should workers check before treating robot training as a career plan?
A listing can be a useful description of one opening, but it is not enough to judge the reliability of a career path. Before leaving a current job or paying for training, seek concrete information about the specific employer and role:
Rank #4
- Al-Driven & Raspberry Pi Powered. TonyPi is a high-performance AI vision robot designed for AI education applications. It is powered by the Raspberry Pi 5, integrated with an OpenCV image processing library and robotic inverse kinematics algorithms. Offering open-source access, TonyPi provides a flexible development environment that supports advanced AI robotics development.
- AI Large Model ChatGPT Integration for Enhanced User-Machine Interaction. TonyPi incorporates a multimodal model, with ChatGPT at the core of its interaction system. With AI vision and voice integration, TonyPi excels in perception, reasoning, and action, enabling advanced embodied AI applications and delivering a seamless, intuitive human-machine interaction experience!
- AI Voice Command & Recognition. Equipped with Large Language Models, TonyPi accurately understands voice commands, analyzes visual scenes in its field of view, and carries out appropriate actions—enabling smooth and responsive voice interaction.
- AI Vision Recognition and Tracking. TonyPi's 2DOF head is fitted with an HD camera that provides a wide field of view. It supports a range of AI vision capabilities, including color recognition, target tracking, ball kicking, line following, and MediaPipe-based motion control for interactive AI applications.
- Comprehensive Learning Resources. TonyPi offers abundant educational content, including resources on robotic motion control, OpenCV, deep learning, MediaPipe, AI large models, voice interaction, and sensor applications. We provide extensive learning materials and tutorials to guide you from foundational concepts to advanced practices, helping you develop your AI humanoid robot.
- Employment terms: Confirm whether the role is permanent, fixed-term, contract, or shift-based, and ask what happens when a project or data-collection phase ends.
- Actual duties: Ask how much time is spent teleoperating, labeling or reviewing data, maintaining equipment, and reporting problems. A title alone does not establish the work mix.
- Training and prerequisites: Get the employer’s stated requirements in writing. The two cited listings do not establish a general degree requirement or a standard credential for this work.
- Pay and progression: Compare the offer’s pay, hours, benefits, and advancement prospects with the costs and risks of leaving current employment. The cited listings do not provide a basis for general pay expectations.
- Monitoring and data: Ask what the equipment records, who can access the collected data, and how worker performance or activity is monitored.
- Safety: Check what training, supervision, stop procedures, and incident reporting apply when working near a robot or wearing teleoperation equipment.
How should employers introduce robots without shifting risk onto workers?
Robot deployment affects work design as well as equipment. Eurofound’s 2024 report recommends involving affected workers and providing training in digital literacy, adaptability, and human–robot collaboration. Worker input can help surface practical problems in a workflow before they become routine or unsafe, while training should match the tasks employees are actually expected to perform.
Safety deserves particular attention in physically demanding workplaces. GAO reported that workers in warehousing, manufacturing, and construction experienced more than 700,000 nonfatal injuries and more than 2,000 fatal accidents in 2022. Those figures describe the sectors’ injury burden; they do not show that robots would prevent those incidents. GAO’s 2024 overview of workplace wearables noted possible benefits for some workers with musculoskeletal discomfort, while its 2025 assessment found limited evidence that wearables reduce injuries. Monitoring or wearable technology should therefore not be treated as proof that a robotic workplace is safe.
When evaluating a deployment, employers and workers should look for measured results over time, not just vendor claims: whether the robot assists or substitutes for workers, what training and worker participation are provided, what safety procedures are in place, and what data are collected. Injury and employment outcomes need to be assessed for the particular workplace; evidence about industrial robots, wearables, or broad robotics forecasts cannot by itself answer what a humanoid deployment will do.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
