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Tesla Bot job postings go live for California and Texas

(Credit: Tesla Bot)

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Tesla has posted new jobs for its Tesla Bot team on its Careers page. Most of the Tesla Bot jobs are located in California except one located in Austin, Texas. 

A few of the openings have been posted for quite some time. Tesla has been steadily posting jobs for the Tesla Bot team since the project was announced during Artificial Intelligence or AI Day back in August. Most of the new jobs seem to be related to software development for the Tesla Bot, hinting at the company’s progress with the humanoid robot.

The new Tesla Bot jobs are listed below with their responsibilities.

Autonomy – Tesla Bot 

Responsibilities

  •   Build, integrate, and deploy real-time state-of-the-art perception models and algorithms into existing system architecture 
  • · Develop online and offline state estimation algorithms by fusing information from cameras, IMUs, and other sensors 
  • · Test and debug your solutions in realistic situations including in customer applications 
  • · Validate and document performance of algorithms and models in real and simulated environments 
  • · Design and build automatic data pipelines that create high quality, unbiased ground truth labels for neural network model training and deployment 
  • · Create robust sensor calibration routines that perform reliably in complex and unpredictable environments 

Software Engineer – Tesla Bot

 Responsibilities 

  • Build a software stack that will control multiple types of mobile robots/vehicles, including Tesla commercial vehicles (M3/MY/Semi), Tesla custom built wheeled indoor robots, other multi degree of freedom robots, and third party mobile robots 
  • Design, extend & review software architecture, and implement on systems through integration, test and real-time deployment 
  • Make performance and optimization trade-offs to meet product requirements 
  • Collaborate and communicate complex technical concepts through quality documentation 
  • Work cross functionally with mechanical, electrical, software, and manufacturing engineering groups 
  • Support the existing software stack and help troubleshoot issues that might occur 

Mechanical Design Engineer – Tesla Bot 

Responsibilities

  • Design and optimize joints and structures for mass, stiffness, cost, and manufacturing 
  • Collaborate with a multi-disciplinary team to create a cohesive and balanced product 
  • Fabricate prototypes, iterate rapidly, advance your concepts through to volume production 
  • Develop specifications and accelerated test plans to validate the product for its determined lifetime 

Embedded Firmware Engineer – Tesla Bot 

Responsibilities

  • Research, design, simulate, specify, implement, debug, and test high speed interfacing buses to multi-in/out systems comprising electromechanical actuators and sensors 
  • Efficiently Translate the modeling team’s control loops and algorithms for implementation on computational hardware (available or newly designed) 
  • Work collaboratively with electrical, mechanical, and controls engineers to define throughput requirements, computational system capabilities, and set targets product roadmaps
  • Advance Tesla IP in developing internal high-throughput sensors and actuators networks for new products 

Previously, Tesla posted jobs for other positions in the Tesla Bot team, including the openings listed below. 

  • Mechanical Engineer – Actuator Gear Design
  • Mechanical Enginee – Actuator Integration
  • Senior Humanoid Mechatronic Robotic Architect 
  • Senior Humanoid Modeling Robotics Architect

Tesla appointed Chris Walti as the company’s Manager of the Mobile Robotics team. Walti posted more jobs via his LinkedIn a few months ago. The openings Tesla was looking for back then included a Controls Engineer, Engineering Technicians, and a Test Engineer based in Texas. 

Tesla also posted a few internship positions for the Summer of 2022. Mobile Robotics internships are open for Autonomy, Software Engineering, Controls Engineering, Firmware Engineering, and Electrical Engineering.

As this year comes to an end, the Tesla Bot team will probably be as busy as ever, burning the midnight oil. After all, the Tesla Bot prototype’s release date is expected for 2022. 

The Teslarati team would appreciate hearing from you. If you have any tips, reach out to me at maria@teslarati.com or via Twitter @Writer_01001101.

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Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Tesla crosses major Unsupervised Self-Driving milestone

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Credit: Tesla

Tesla has reached a notable benchmark in its autonomous driving program after its Robotaxi fleet surpassed one million miles of unsupervised operation. The company made the announcement during its Cybercab event in Austin on September 3.

Tesla Vice President of AI Ashok Elluswamy told attendees he was happy to report the fleet had achieved one million miles of unsupervised Robotaxi operation as a testament to safety.

The new total marked a sharp increase from the 380,000 unsupervised miles Tesla disclosed during its second-quarter 2026 earnings update in late July.

In roughly six weeks, the company added about 620,000 miles. That acceleration followed Tesla’s decision to remove in-vehicle safety monitors from most of its operations outside the San Francisco Bay Area.

Credit: Tesla

Tesla first launched Robotaxi service in Austin in June 2025 with safety drivers present. It later began fully unsupervised rides and expanded into Dallas, Houston, Miami, Orlando, and Tampa. The San Francisco Bay Area remains the exception, where a safety monitor still rides in the vehicle under California permitting rules.

The company has not released a city-by-city breakdown of the one million unsupervised miles.

The milestone arrived as Tesla began offering public Cybercab rides in Austin. The purpose-built vehicle has no steering wheel or pedals and is designed only for autonomous ride-hailing. Production versions joined the existing fleet of modified Tesla vehicles already operating in the service.

Tesla’s unsupervised mileage is growing at a double-digit weekly rate according to earlier company comments, yet its fleet size remains modest compared with established competitors. Waymo has accumulated more than 200 million fully autonomous rider-only miles. Tesla has described its own unsupervised operations as having recorded zero notable incidents in the period leading up to the July update.

The one-million-mile figure reflects Tesla’s shift from supervised testing to broader driverless service in multiple states. It also highlights the company’s strategy of using both existing Model Y vehicles and the new Cybercab to scale its network.

Credit: Tesla

Whether the rapid recent growth continues will depend on further city expansions, regulatory approvals, and the performance of the purpose-built Cybercab in everyday paid rides. Tesla has not specified how many of the latest miles involved the new vehicle versus the rest of the fleet.

The announcement underscores Tesla’s progress toward a larger robotaxi network while illustrating the remaining gap in total autonomous experience relative to longer-operating rivals.

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Tesla Robotaxi will be a 24/7 service: here’s when

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Credit: @AdanGuajardo/X

Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.

The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.

That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.

Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.

Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.

By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.

Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.

Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.

If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.

That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.

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Tesla Full Self-Driving will now overtake manual driving to avoid disaster

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Credit: Tesla

Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.

Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.

The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.

The intervention is meant as a last-resort safety net, not a replacement for attentive driving.

Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident

Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.

After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.

The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.

Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.

The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.

If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.

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