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.
Elon Musk
Tesla confirms that work on Dojo 3 has officially resumed
“Now that the AI5 chip design is in good shape, Tesla will restart work on Dojo 3,” Elon Musk wrote in a post on X.
Tesla has restarted work on its Dojo 3 initiative, its in-house AI training supercomputer, now that its AI5 chip design has reached a stable stage.
Tesla CEO Elon Musk confirmed the update in a recent post on X.
Tesla’s Dojo 3 initiative restarted
In a post on X, Musk said that with the AI5 chip design now “in good shape,” Tesla will resume work on Dojo 3. He added that Tesla is hiring engineers interested in working on what he expects will become the highest-volume AI chips in the world.
“Now that the AI5 chip design is in good shape, Tesla will restart work on Dojo3. If you’re interested in working on what will be the highest volume chips in the world, send a note to AI_Chips@Tesla.com with 3 bullet points on the toughest technical problems you’ve solved,” Musk wrote in his post on X.
Musk’s comment followed a series of recent posts outlining Tesla’s broader AI chip roadmap. In another update, he stated that Tesla’s AI4 chip alone would achieve self-driving safety levels well above human drivers, AI5 would make vehicles “almost perfect” while significantly enhancing Optimus, and AI6 would be focused on Optimus and data center applications.
Musk then highlighted that AI7/Dojo 3 will be designed to support space-based AI compute.
Tesla’s AI roadmap
Musk’s latest comments helped resolve some confusion that emerged last year about Project Dojo’s future. At the time, Musk stated on X that Tesla was stepping back from Dojo because it did not make sense to split resources across multiple AI chip architectures.
He suggested that clustering large numbers of Tesla AI5 and AI6 chips for training could effectively serve the same purpose as a dedicated Dojo successor. “In a supercomputer cluster, it would make sense to put many AI5/AI6 chips on a board, whether for inference or training, simply to reduce network cabling complexity & cost by a few orders of magnitude,” Musk wrote at the time.
Musk later reinforced that idea by responding positively to an X post stating that Tesla’s AI6 chip would effectively be the new Dojo. Considering his recent updates on X, however, it appears that Tesla will be using AI7, not AI6, as its dedicated Dojo successor. The CEO did state that Tesla’s AI7, AI8, and AI9 chips will be developed in short, nine-month cycles, so Dojo’s deployment might actually be sooner than expected.
Elon Musk
Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online
Elon Musk shared his update in a recent post on social media platform X.
xAI has brought its Colossus 2 supercomputer online, making it the first gigawatt-scale AI training cluster in the world, and it’s about to get even bigger in a few months.
Elon Musk shared his update in a recent post on social media platform X.
Colossus 2 goes live
The Colossus 2 supercomputer, together with its predecessor, Colossus 1, are used by xAI to primarily train and refine the company’s Grok large language model. In a post on X, Musk stated that Colossus 2 is already operational, making it the first gigawatt training cluster in the world.
But what’s even more remarkable is that it would be upgraded to 1.5 GW of power in April. Even in its current iteration, however, the Colossus 2 supercomputer already exceeds the peak demand of San Francisco.
Commentary from users of the social media platform highlighted the speed of execution behind the project. Colossus 1 went from site preparation to full operation in 122 days, while Colossus 2 went live by crossing the 1-GW barrier and is targeting a total capacity of roughly 2 GW. This far exceeds the speed of xAI’s primary rivals.
Funding fuels rapid expansion
xAI’s Colossus 2 launch follows xAI’s recently closed, upsized $20 billion Series E funding round, which exceeded its initial $15 billion target. The company said the capital will be used to accelerate infrastructure scaling and AI product development.
The round attracted a broad group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group. Strategic partners NVIDIA and Cisco also continued their support, helping xAI build what it describes as the world’s largest GPU clusters.
xAI said the funding will accelerate its infrastructure buildout, enable rapid deployment of AI products to billions of users, and support research tied to its mission of understanding the universe. The company noted that its Colossus 1 and 2 systems now represent more than one million H100 GPU equivalents, alongside recent releases including the Grok 4 series, Grok Voice, and Grok Imagine. Training is also already underway for its next flagship model, Grok 5.
Elon Musk
Tesla AI5 chip nears completion, Elon Musk teases 9-month development cadence
The Tesla CEO shared his recent insights in a post on social media platform X.
Tesla’s next-generation AI5 chip is nearly complete, and work on its successor is already underway, as per a recent update from Elon Musk.
The Tesla CEO shared his recent insights in a post on social media platform X.
Musk details AI chip roadmap
In his post, Elon Musk stated that Tesla’s AI5 chip design is “almost done,” while AI6 has already entered early development. Musk added that Tesla plans to continue iterating rapidly, with AI7, AI8, AI9, and future generations targeting a nine-month design cycle.
He also noted that Tesla’s in-house chips could become the highest-volume AI processors in the world. Musk framed his update as a recruiting message, encouraging engineers to join Tesla’s AI and chip development teams.
Tesla community member Herbert Ong highlighted the strategic importance of the timeline, noting that faster chip cycles enable quicker learning, faster iteration, and a compounding advantage in AI and autonomy that becomes increasingly difficult for competitors to close.
AI5 manufacturing takes shape
Musk’s comments align with earlier reporting on AI5’s production plans. In December, it was reported that Samsung is preparing to manufacture Tesla’s AI5 chip, accelerating hiring for experienced engineers to support U.S. production and address complex foundry challenges.
Samsung is one of two suppliers selected for AI5, alongside TSMC. The companies are expected to produce different versions of the AI5 chip, with TSMC reportedly using a 3nm process and Samsung using a 2nm process.
Musk has previously stated that while different foundries translate chip designs into physical silicon in different ways, the goal is for both versions of the Tesla AI5 chip to operate identically. AI5 will succeed Tesla’s current AI4 hardware, formerly known as Hardware 4, and is expected to support the company’s Full Self-Driving system as well as other AI-driven efforts, including Optimus.