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Tesla posts nearly 30 Dojo jobs and 2 internships

(Credit: Tesla)

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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.

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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.

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’s two defunct flagship models are getting a big upgrade

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Tesla’s two recently-defunct flagship models, the Model S and Model X, are getting a big upgrade, according to the company’s Head of AI, Ashok Elluswamy.

Older Hardware 3 Model S and Model X vehicles have been the last major holdouts in Tesla’s Full Self-Driving v14 Lite rollout, and that wait now appears to be ending.

Tesla brings closure to flagship ‘sentimental’ models, Musk confirms

At Tesla’s Cybercab launch, AI chief Ashok Elluswamy told Ryan McCaffrey that he thought the S and X build “was supposed to go out last week.” Evidently, Elluswamy expects the suite to be rolled out to those HW3 Model S and Model X very soon:

Those cars are not the current Model S and Model X, which already ship with Hardware 4. They are the pre-refresh flagships built around Tesla’s older Autopilot computer, often called HW3 or AI3.

Tesla stopped putting that computer in new vehicles years ago, which is why owners treat these S and X cars as a closed generation. Model 3 and Model Y vehicles on the same computer began receiving v14 Lite in late June 2026 and saw a wider North American expansion in July. South Korea followed as an early international market. The S and X versions of the same software never joined that wave.

v14 Lite is Tesla’s way of squeezing the current v14 driving stack onto hardware that cannot run the full AI 4 model. The company describes the process as distillation: behaviors learned on the newer computer, including reinforcement learning and offline models, are compressed so the older chip and cameras can use them as a guide.

Early descriptions put the distilled network at roughly 15 percent of the original size. The result is still supervised Level 2 driving. Tesla has been clear that HW3 cannot support unsupervised Full Self-Driving or robotaxi operation because of memory and bandwidth limits.

The feature list is what made the wait so frustrating for S and X owners, as plenty of new features are to be shipped with it.

Official notes for the first Lite build, firmware 2026.20.5.1, added parking, unparking, and reversing; arrival options for a parking lot, street, driveway, or curbside; speed profiles that stay available at all times; and start-from-park engagement. Tesla also claimed better handling of merges, forks, pedestrians, traffic lights, and cut-ins, plus fewer false slowdowns and smoother lane centering.

A mid-July follow-on build, 2026.20.6.10, added more of the Hardware 4 interface, including a standalone Self-Driving app and the ability to start a trip from Park without a brake-pedal confirmation.

Elluswamy called that version the one “likely going to wide release.”

That wide release already reached most other HW3 cars in the United States and Canada. International timing still depends on regional validation and regulatory approval. For S and X owners, the remaining work appears to be model-specific validation rather than a new software stack.

There is no official Tesla changelog or build number for those two models yet, only Elluswamy’s offhand timeline. Some HW3 drivers who already have Lite report large gains over v12.6; others have described new indecision or phantom braking. The next test will be whether the same software lands cleanly on the older flagships that have waited the longest.

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This tiny Tesla Cybertruck adjustment has big advantages

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Credit: Wes Morrill | X

Yesterday, we reported on Tesla Cybertruck getting some major adjustments from a manufacturing standpoint in an effort to make the all-electric pickup more cost-effective, more reliable, more serviceable, and more easily produced.

Tesla Cybertruck engineer reveals new changes in ‘constantly evolving’ pickup

One of those changes was the addition of a self-reinforcing polypropylene aero shield that sits underneath the truck. Previously, Tesla utilized aluminum for this, but the self-reinforcing polypropylene was more durable while also being cheaper and lighter.

Tesla has revealed another small change it made to the Cybertruck, and it has to do with the side repeater cameras.

Tesla does not wait for a new model year to improve its vehicles. On September 8, Cybertruck lead engineer Wes Morrill posted side-by-side photos of an updated side repeater camera housing now rolling off the line at Gigafactory Texas.

The triangular camera pod mounted on the front fender looks almost identical at first glance. A closer look reveals a revised contour that uses the air already flowing around the truck to keep the lens clearer in rain and road spray.

The side repeater cameras sit in an exposed position on the Cybertruck’s angular stainless-steel body.

In wet weather, they readily collect water droplets that can degrade the image Autopilot and Full Self-Driving use for lane changes and blind-spot monitoring. Early production trucks sometimes left owners wiping lenses by hand or accepting temporary restrictions on driver-assistance features.

Tesla has added washers to cameras on certain other models and on Cybercab prototypes, but those active systems add cost, complexity, and extra potential leak points.

The new housing solves the problem with passive geometry. Subtle changes in the surround create localized airflow disturbances as the vehicle moves. Those eddies physically push water droplets away from the optical surface. Morrill called the result “pure vision improvement” achieved at “no cost penalty.” Once the production mold is updated, every subsequent part costs the same as the original.

The advantages compound quickly. Clearer cameras in rain improve the reliability of driver-assistance features precisely when they are needed most. The design consumes no extra energy and introduces no new failure modes.

New Cybertrucks built after the tooling changeover receive the updated part automatically. Some owners of trucks delivered as late as June 2026 have already confirmed they received the revised housing. Retrofit questions have appeared in replies, and the cameras appear electrically compatible, though Tesla has not announced an official service program.

A few millimeters of reshaped housing will not make headlines the way a new battery pack does, but these changes are incremental and increase the Cybertruck’s effectiveness as a vehicle over time.

This improvement illustrates how Tesla continues to refine the Cybertruck after volume production began. Better wet-weather vision, zero added cost, and no extra hardware add up to a meaningful gain in everyday usability and safety.

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Tesla is rolling out a new FSD version with a massive safety addition

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Credit: Tesla

Tesla is rolling out a new version of its Full Self-Driving suite to some owners that comes with the massive addition of a safety feature.

Tesla is rolling out Automatic Collision Evasion with the 2026.27.6 Software Update, which started rolling out to some vehicles last night. We received the update, along with Full Self-Driving v14.3.9, as well as v14.2 Lite, which has identical release notes as the previous version and seems to have some refinements and improvements in behavior and performance.

However, most of the attention has fallen on the Automatic Collision Evasion feature, which we covered in an article last week.

The function will activate Full Self-Driving to “try to keep your vehicle safe and then continue driving. It can engage in the following situations while you are driving manually:

  • Scenario 1: A frontal collision is imminent and braking alone may not avoid it.
  • Scenario 2: Your vehicle detects that you are not sufficiently attentive to the road (for example, reaching toward the back seat), or that Full Self-Driving (Supervised) may have been unintentionally disengaged.”

Essentially, FSD will take over when the vehicle determines you are not paying sufficient attention or are heading toward a potential collision. The addition of this feature is incredibly useful as distracted driving is a major issue in today’s world.

Along with the new safety feature is Tesla FSD v14.3.9, which has no additional release notes compared to the previous version, but in my first drives, my first impression is that operation is great, and parking is still sort of a pain point.

Additionally, Tesla v14.2. Lite has arrived. A great review of that is available here:


The addition of an Automatic Collision Evasion feature is similar to that of other collision avoidance systems that are used by companies like Hyundai, Kia, and Genesis. These programs typically utilize radar and camera sensors to apply emergency brakes autonomously, though evasive steering in a manual driving mode is pioneered primarily by Tesla’s newest addition.

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