Tesla recently posted nearly 30 jobs and 2 internships related to Dojo. Most of the Tesla Dojo positions are in Palo Alto, California. Tesla posted one Dojo-related job in Texas and another in Colorado.
Tesla is looking for a Sr. DFT Verification Engineer and Sr. DFT Engineer in Austin, Texas. The Dojo team is looking for a Staff Physical Design Engineer in Fort Collins, Colorado.
Besides the two jobs in Texas, Tesla’s Dojo team is also searching for a few people to fill senior positions in Palo Alto, California, including a Sr. Site Reliability Engineer, Sr. Design Verification Engineer, and Sr. Firmware Engineer.
Tesla also wants to welcome interns to the Dojo team for the summer of 2025. The company is specifically looking for Performance Modeling Engineers and future Technical Program Managers.
Performance Modeling Engineer Internship Description
This position is expected to start around May 2025 and continue through the Summer term (approximately August 2025) or into Fall 2025 if available and there is an opportunity to do so. We ask for a minimum of 12 weeks, full-time and on-site, for most internships. Our internship program is for students who are actively enrolled in an academic program. Recent graduates seeking employment after graduation and not returning to school should apply for full-time positions, not internships.
International Students: If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. You must be able to work 40 hours per week on-site. Many students will be limited to part-time during the academic year.
Location: Palo Alto, CA
As an intern on the Dojo Performance Modeling team, you will play an integral part in efficiently running Tesla’s neural networks on our in-house custom-silicon supercomputer system. You will be involved in tasks like running ML benchmarks to analyze and debug performance bottlenecks, develop new tests and build the infrastructure to automate these processes. We are looking for a motivated engineering student that is excited by the work Tesla is doing in pushing the envelope of real-world AI. The ideal candidate will have a strong background in computer architecture, analytical and cycle-based simulation, and AI workloads, with a passion for high-performance computing and complex systems modeling.
Performance Modeling Engineer Responsibilities
- Develop and validate microarchitecture simulations of a massively parallel machine for AI training, including system architecture, core architecture, memory hierarchy, and interconnects.
- Write, debug, and maintain robust infrastructure code for validating the Dojo performance.
- Create and maintain performance dashboards on the Dojo system.
- Collaborate with architects and engineers to understand the requirements of the simulation and ensure that it accurately models the behavior of the system.
- Develop and maintain software frameworks and tools to support testing and deployment.
- Participate in code reviews, testing, and debugging to ensure high-quality software.
Technical Program Manager (DOJO & AI Hardware) Internship Description
This position is expected to start around May 2025 and continue through the Summer term (approximately August 2025) or into Fall 2025 if available and there is an opportunity to do so. We ask for a minimum of 12 weeks, full-time and on-site, for most internships. Our internship program is for students who are actively enrolled in an academic program. Recent graduates seeking employment after graduation and not returning to school should apply for full-time positions, not internships.
International Students: If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. You must be able to work 40 hours per week on-site. Many students will be limited to part-time during the academic year.
Location: Palo Alto, CA
Technical Program Manager (DOJO & AI Hardware) Internship Responsibilities
- Currently pursuing a degree in Mechanical, Electrical, Computer Science Engineering, or a related field
- Prior program management experience or managing a team, such as FSAE, Hyperloop, etc
- Desired to be proficient in Microsoft Office, JIRA, Confluence, and Git
- Experience in leading teams and proven ability to drive initiatives to conclusion
The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.
Tesla has expanded the operational geofence for its driverless Robotaxi service in Austin, Texas, marking the first such increase in some time. The updated Service Area for Robotaxi in Austin now spans about 288 square miles and is roughly 9 percent larger than the previous boundary.
This incremental growth adds approximately 24 square miles of coverage, bringing the prior zone of roughly 264 square miles into a broader footprint that better serves northern suburbs.
The expansion extends the geofence northward toward Pflugerville along the US 183 corridor, incorporating additional neighborhoods north of the Domain and areas such as Mesa Park. These additions include higher-end residential and commercial districts that previously sat just outside the allowed operating zone.
Riders can now request unsupervised trips that begin or end in these newly included locations, provided the entire route remains inside the digital boundary:
Tesla has just expanded its Robotaxi service area in Austin, Texas for the first time in 10 months.
The new service area is roughly 9% larger than the old one, and is about 288 square miles in total. pic.twitter.com/i4oBM1KfWS
— Sawyer Merritt (@SawyerMerritt) August 31, 2026
Tesla first launched public Robotaxi operations in Austin in mid-2025 with a modest initial zone of about 20 square miles. Subsequent enlargements in 2025 and early 2026 steadily grew the map until it covered much of the metropolitan area.
After the last major update roughly ten months earlier, the company held the boundary steady while it collected additional miles and refined the FSD suite.
The modest nine percent increase still matters for daily utility. Longer trips become possible, more residents gain access, and the fleet can accumulate more diverse real-world data across new road types and traffic patterns. Observers note that the added territory aligns with existing Tesla service infrastructure, which could support more efficient vehicle staging in the North end of Austin.
Although the geofence has grown, Tesla continues to operate a relatively small unsupervised fleet in the city. The company has emphasized safety and software readiness over rapid geographic scaling. This latest map update signals that Tesla remains committed to expanding Robotaxi availability in its home market as it prepares for further software improvements and potential Cybercab deployments.
The 288-square-mile zone now gives Austin riders one of the larger driverless service areas currently available in the United States.
Tesla’s 2026 Summer Update turns Grok from a talking companion into a true in-car controller, with considerably expanded capabilities. Where the assistant once answered questions and handled navigation, it can now operate hardware and software through ordinary speech, including several requests at the same time.
Grok has become incredibly robust over the past few quarters, and this new ability that Tesla has included with its Summer Update is perhaps the clearest sign of just how capable it has become.
You can issue many commands to Grok at once, and each will be taken care of: anything from headlight control to climate adjustments to mirror folding can now all be taken care of with a simple sentence spoken toward Grok:
This is cool, you can now give Grok a ton of commands at once in your Tesla and it’ll do them all together.
The commands I gave:
• Fold mirrors
• Turn on wipers to fastest setting
• Change temp to 65°
• Open self-driving app
• Open gloveboxComes with Tesla’s 2026 Summer… pic.twitter.com/drZxoHrknv
— Sawyer Merritt (@SawyerMerritt) August 26, 2026
Here’s another example I used in my Model Y:
🚨 Using Grok to control the cabin temperature and turn on headlights in 2026 Model Y on FSD v14.3.8 and 2026.26.6.5 pic.twitter.com/7clgQkGABk
— TESLARATI (@Teslarati) August 27, 2026
Tesla’s official Release Notes list the core powers of Grok’s new capabilities: Grok can place phone calls from a paired phone, search a streaming service and queue music, adjust climate, and search the Controls panel. Drivers can also ask it questions about the vehicle or the latest features included in a recent software update.
It can also take care of driving settings, dynamics, and other relevant preferences that deal with how the car operates and handles.
Tesla Summer Update begins rolling out: a look at the new features
It’s also more of a use case than a novelty feature. Grok was great for learning about something that was being pondered while Full Self-Driving was taking care of the major automotive responsibilities, but it did have some useful functionality when it came to navigation.
Another less-noted improvement is the swift transition that Grok has from thinking of its answer to giving you one. In the past, it would take a few seconds for Grok to truly come up with a valuable response. It now seems that it is improving, at least slightly.
Tesla Full Self-Driving is set to get a major fix with pothole avoidance, a feature that CEO Elon Musk said recently was “coming soon.” The feature has been included within the FSD v14 release notes for some time as an upcoming improvement.
Potholes come in all shapes and sizes, but one thing is universal about them, and that is the fact that every driver wants to avoid them. Driving into or over a pothole can cause tire and wheel damage, alignment issues, and even, in some more severe instances, injury to occupants or major damage to a vehicle in despair.
Tesla Cybercab uses a unique strategy for picking up the right rider
Musk said late last night in a post that pothole avoidance while utilizing the Full Self-Driving suite is “coming soon.”
Coming soon
— Elon Musk (@elonmusk) August 31, 2026
Full Self-Driving, even in its most recent and robust forms, still has its shortcomings. While the suite has performed exceptionally well with avoiding on-road obstacles like cardboard boxes, horse droppings, car parts, and other debris, it still seems to struggle with recognizing certain things.
Potholes and other abrupt changes in a road’s layout are things that FSD still tends to struggle with. Perhaps the suite’s 3D modeling is still in need of some additional data or some sort of script that will help it to avoid a potentially destructive pothole or bump in the road that would be easily recognizable by the human eye.
Musk has mentioned pothole avoidance for some time, with the initial idea coming in April 2019 when an owner first requested the feature. Musk said that Tesla would “definitely” develop pothole avoidance.
In August 2020, Musk said Tesla was in the process of labeling bumps and potholes so cars can either slow down or steer around them altogether.
Tesla to utilize micro maps for pothole-detection in future update
Avoiding major disturbances in the road is a necessary feature for Full Self-Driving to have, especially as Tesla is working toward a fully autonomous program that will eventually allow every occupant in the vehicle to sleep, work, or enjoy leisure time while traveling.
That truly begins this week with the launch of Cybercab on Thursday.
Tesla expands driverless Robotaxi geofence in Austin
Elon Musk’s Grok can basically control anything in your Tesla now
