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Job postings can be a great source of intel on what kind of product development it’s undertaking. So let’s look into the recent Data Collection Operator job listing from Tesla…

It’s more than just a job posting…
Job postings can be a great source of intel on where a company is investing heavily and what kind of product development it’s undertaking.
It doesn’t matter if a company is public or private… most jobs tend to be posted either on a company website, a job board, or even on X (Twitter).
So for companies we’re watching or researching closely, it’s always good to keep an eye on where they’re hiring and what they’re focused on.
A great example is a series of job postings at Tesla Optimus, Tesla’s robotics division, that has been the target of much criticism. (Note: The haters will be deeply humbled within 12 months).

Tesla (TSLA) has been hiring Data Collection Operators for its Tesla Optimus project. Reportedly, more than 50 have already been hired.
This is a completely new kind of job created to support the development of Optimus. As we can see above, it’s an “Entry-Level” position. And detailed in the job posting is a compensation range of $25–48/hour in addition to cash and stock awards plus benefits.
This is a fantastic, high-paying, entry-level job supporting the bleeding edge of autonomous robotics technology… and it’s at one of the greatest high-tech companies in history.
But aside from being a great entry-level job opportunity, the job description tells us a lot more about what’s going on behind the scenes.
Here are some key job responsibilities:
Some of the job requirements are even more telling:
As it turns out, the job title is descriptive. Given the responsibilities and requirements, it’s clear that the purpose of hiring so many data collection operators (and supervisors) is to accelerate the collection of video and data of humans performing real-world tasks.
And keen eyes will notice in the job posting that there are three shifts throughout the day for the position: 8–4:30 PM, 4–12:30 AM, and 12–8:30 AM. The Tesla Optimus team is literally working around the clock… how’s that for acceleration?
The purpose of this job will be to train the neural network that will become Optimus’ “brain.”
Operators have height requirements that are consistent with Optimus’ height (5’8”) and standard motion capture suit sizes.
Tesla is not just capturing how humans solve a specific task using arms and fingers (this is the motion capture), it is capturing the video of how we use our vision to assist in identification, analysis, problem-solving, and task completion.
Operators will clearly be navigating the real world by foot (7+ hours a day) and traveling (up to 25% of the time) to collect data in a wide range of real-world environments.
The picture below provides us with a simple visual of what the data collection gear looks like for the operator. It’s loaded with sensors, cameras, and a virtual reality headset.

Source: Tesla
Tesla’s choice of technology tells us a lot about its approach to developing Optimus. The motion capture suits will train Optimus how to move naturally to solve problems and navigate the real world.
The key to its autonomy, however, is vision. Tesla is building upon its full self-driving (FSD) software developed for its electric vehicles by training its neural network on hundreds of thousands of hours of training video, which is why it needs to hire so many data collectors.
Musk and his team at Tesla have long maintained that light detection and ranging – aka LiDAR – technology was not necessary for autonomous driving.
This was a highly controversial technological approach in the industry. One that caused most “experts” to predict that Tesla would fail.
But Tesla went one step further. In 2021, Tesla removed radar from its Model 3 and Model Y EVs and then did the same for Model S and Model X in 2022.
Also in 2022, Tesla removed ultrasonic sensors from Model 3 and Model Y, and in 2023 did the same for Model S and Model X.
At this point, Tesla’s full self-driving technology is built entirely on vision. The neural network has absorbed billions of miles of training video from Teslas driving on Autopilot and full self-driving.
The autonomous driving team at Tesla has demonstrated that vision isn’t just sufficient for autonomous driving, but it can outperform vehicles that are loaded with LiDAR, radar, and ultrasonic sensors.
Vision and neural network technology is the key to autonomy.
Whether it’s a car, truck, semi, or humanoid robot, without mastering it… good luck.
Tesla has already mastered the most difficult technological challenge with its autonomous driving software built on vision. Now it is training its humanoid robot AI on an enhanced vision data set designed to teach skills and everyday tasks.
Optimus needs our help.
If I wasn’t 6’2”, I’d probably sign up myself to join the team. How incredible would it be to be part of a team making history with Optimus? And it’s an incredible opportunity for those who are either early in their career or looking for a career change.
It’s a great example of how this new industry is already creating jobs. And we’re going to need millions of workers on a global scale to help service and maintain our newfound collaborative robots (cobots) – a very obvious form of Manifested AI.
Robots, whether or not they are humanoid or otherwise, are machines. And they need to be maintained. Just as a car, truck, tractor, or excavator needs human labor to clean and maintain, so will robots.
This is a billion-plus unit market opportunity for autonomous humanoid robots. And with it comes not just opportunity for Tesla, but for those companies that provide components for Optimus like cameras, sensors, semiconductors, and power ICs.
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