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.




News
Tesla is not sparing any expense in ensuring the Cybercab is safe
Images shared by the longtime watcher showed 16 Cybercab prototypes parked near Giga Texas’ dedicated crash test facility.
The Tesla Cybercab could very well be the safest taxi on the road when it is released and deployed for public use. This was, at least, hinted at by the intensive safety tests that Tesla seems to be putting the autonomous two-seater through at its Giga Texas crash test facility.
Intensive crash tests
As per recent images from longtime Giga Texas watcher and drone operator Joe Tegtmeyer, Tesla seems to be very busy crash testing Cybercab units. Images shared by the longtime watcher showed 16 Cybercab prototypes parked near Giga Texas’ dedicated crash test facility just before the holidays.
Tegtmeyer’s aerial photos showed the prototypes clustered outside the factory’s testing building. Some uncovered Cybercabs showed notable damage and one even had its airbags engaged. With Cybercab production expected to start in about 130 days, it appears that Tesla is very busy ensuring that its autonomous two-seater ends up becoming the safest taxi on public roads.
Prioritizing safety
With no human driver controls, the Cybercab demands exceptional active and passive safety systems to protect occupants in any scenario. Considering Tesla’s reputation, it is then understandable that the company seems to be sparing no expense in ensuring that the Cybercab is as safe as possible.
Tesla’s focus on safety was recently highlighted when the Cybertruck achieved a Top Safety Pick+ rating from the Insurance Institute for Highway Safety (IIHS). This was a notable victory for the Cybertruck as critics have long claimed that the vehicle will be one of, if not the, most unsafe truck on the road due to its appearance. The vehicle’s Top Safety Pick+ rating, if any, simply proved that Tesla never neglects to make its cars as safe as possible, and that definitely includes the Cybercab.
Elon Musk
Tesla’s Elon Musk gives timeframe for FSD’s release in UAE
Provided that Musk’s timeframe proves accurate, FSD would be able to start saturating the Middle East, starting with the UAE, next year.
Tesla CEO Elon Musk stated on Monday that Full Self-Driving (Supervised) could launch in the United Arab Emirates (UAE) as soon as January 2026.
Provided that Musk’s timeframe proves accurate, FSD would be able to start saturating the Middle East, starting with the UAE, next year.
Musk’s estimate
In a post on X, UAE-based political analyst Ahmed Sharif Al Amiri asked Musk when FSD would arrive in the country, quoting an earlier post where the CEO encouraged users to try out FSD for themselves. Musk responded directly to the analyst’s inquiry.
“Hopefully, next month,” Musk wrote. The exchange attracted a lot of attention, with numerous X users sharing their excitement at the idea of FSD being brought to a new country. FSD (Supervised), after all, would likely allow hands-off highway driving, urban navigation, and parking under driver oversight in traffic-heavy cities such as Dubai and Abu Dhabi.
Musk’s comments about FSD’s arrival in the UAE were posted following his visit to the Middle Eastern country. Over the weekend, images were shared online of Musk meeting with UAE Defense Minister, Deputy Prime Minister, and Dubai Crown Prince HH Sheikh Hamdan bin Mohammed. Musk also posted a supportive message about the country, posting “UAE rocks!” on X.
FSD recognition
FSD has been getting quite a lot of support from foreign media outlets. FSD (Supervised) earned high marks from Germany’s largest car magazine, Auto Bild, during a test in Berlin’s challenging urban environment. The demonstration highlighted the system’s ability to handle dense traffic, construction sites, pedestrian crossings, and narrow streets with smooth, confident decision-making.
Journalist Robin Hornig was particularly struck by FSD’s superior perception and tireless attention, stating: “Tesla FSD Supervised sees more than I do. It doesn’t get distracted and never gets tired. I like to think I’m a good driver, but I can’t match this system’s all-around vision. It’s at its best when both work together: my experience and the Tesla’s constant attention.” Only one intervention was needed when the system misread a route, showcasing its maturity while relying on vision-only sensors and over-the-air learning.
News
Tesla quietly flexes FSD’s reliability amid Waymo blackout in San Francisco
“Tesla Robotaxis were unaffected by the SF power outage,” Musk wrote in his post.
Tesla highlighted its Full Self-Driving (Supervised) system’s robustness this week by sharing dashcam footage of a vehicle in FSD navigating pitch-black San Francisco streets during the city’s widespread power outage.
While Waymo’s robotaxis stalled and caused traffic jams, Tesla’s vision-only approach kept operating seamlessly without remote intervention. Elon Musk amplified the clip, highlighting the contrast between the two systems.
Tesla FSD handles total darkness
The @Tesla_AI account posted a video from a Model Y operating on FSD during San Francisco’s blackout. As could be seen in the video, streetlights, traffic signals, and surrounding illumination were completely out, but the vehicle drove confidently and cautiously, just like a proficient human driver.
Musk reposted the clip, adding context to reports of Waymo vehicles struggling in the same conditions. “Tesla Robotaxis were unaffected by the SF power outage,” Musk wrote in his post.
Musk and the Tesla AI team’s posts highlight the idea that FSD operates a lot like any experienced human driver. Since the system does not rely on a variety of sensors and a complicated symphony of factors, vehicles could technically navigate challenging circumstances as they emerge. This definitely seemed to be the case in San Francisco.
Waymo’s blackout struggles
Waymo faced scrutiny after multiple self-driving Jaguar I-PACE taxis stopped functioning during the blackout, blocking lanes, causing traffic jams, and requiring manual retrieval. Videos shared during the power outage showed fleets of Waymo vehicles just stopping in the middle of the road, seemingly confused about what to do when the lights go out.
In a comment, Waymo stated that its vehicles treat nonfunctional signals as four-way stops, but “the sheer scale of the outage led to instances where vehicles remained stationary longer than usual to confirm the state of the affected intersections. This contributed to traffic friction during the height of the congestion.”
A company spokesperson also shared some thoughts about the incidents. “Yesterday’s power outage was a widespread event that caused gridlock across San Francisco, with non-functioning traffic signals and transit disruptions. While the failure of the utility infrastructure was significant, we are committed to ensuring our technology adjusts to traffic flow during such events,” the Waymo spokesperson stated, adding that it is “focused on rapidly integrating the lessons learned from this event, and are committed to earning and maintaining the trust of the communities we serve every day.”