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Overnight Autonomous Vehicle Testing information

What is overnight autonomous vehicle testing?

Overnight Autonomous Vehicle Testing jobs involve monitoring, operating, and collecting data from self-driving vehicles during nighttime hours. Employees in these roles ensure the vehicles perform safely and efficiently according to testing protocols, often working with engineers to report issues or anomalies. These positions may require sitting in or near the vehicle, intervening when necessary, and documenting observations for further analysis. Overnight schedules allow companies to maximize testing hours while minimizing daytime traffic interference. Candidates typically need a valid driver's license, good attention to detail, and sometimes technical or engineering backgrounds.

What are some common challenges faced by overnight autonomous vehicle testers, and how can they be addressed?

Overnight autonomous vehicle testers often encounter challenges such as fatigue due to late hours, managing unexpected technical issues in low-traffic conditions, and maintaining effective communication with remote engineering teams. To address these, testers should prioritize proper rest before shifts, follow safety protocols diligently, and stay connected through real-time reporting tools. Developing strong situational awareness and adaptability also helps testers respond efficiently to any anomalies during overnight operations.

What are the key skills and qualifications needed to thrive as an overnight autonomous vehicle testing specialist?

To thrive in Overnight Autonomous Vehicle Testing, you need a solid understanding of automotive systems, safety protocols, and a valid driver’s license, often supported by a technical or engineering background. Familiarity with data logging tools, vehicle diagnostic software, and autonomous driving platforms is typically required. Strong attention to detail, effective communication, and the ability to remain alert during overnight shifts are essential soft skills. These skills ensure accurate data collection, safe operation, and the ability to troubleshoot issues in real-time, which are critical for the reliable testing and advancement of autonomous vehicle technology.

What are the most commonly searched types of Autonomous Vehicle Testing jobs in California?

The most popular types of Autonomous Vehicle Testing jobs in California are:

What cities in California are hiring for Overnight Autonomous Vehicle Testing jobs?

Cities in California with the most Overnight Autonomous Vehicle Testing job openings:

Overnight Autonomous Vehicle Testing jobs near you
Infographic showing various Overnight Autonomous Vehicle Testing job openings in California as of August 2026, with employment types broken down into 50% Full Time, 17% Part Time, and 33% Contract. Highlights an 100% In-person job distribution.

Senior Solutions Architect - Autonomous Vehicles

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

Re-posted 10 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 244 rated software companies

Job description

Join the NVIDIA's Solutions Engineering team that is reshaping the future of driving! Our goal is to build and deploy scalable solutions for autonomous vehicles and as a result, create safer and more efficient roads. Our team is hands-on, passionate about practical results, and values diversity. We are looking for solutions architects, who are experts, trusted technical advisors and leaders to our partners and customers, that believe in deep learning, data science, and artificial intelligence will transform autonomous driving. We need individuals who can enable customer productivity, develop positive relationships with our technology partners and collaborate with internal teams to develop the best solutions for partners working on our platform.
NVIDIA is widely considered to be one of the technology world's most desirable employers. If you are passionate in bringing autonomous vehicles into the world and see the solution come together, we would like to hear from you!
What you'll be doing:
  • Lead vehicle software integration and bring-up activities, collaborating with internal and external partner teams to develop and launch autonomous vehicle solutions.
  • Drive use case analysis, functional requirements' definition, critical metric definition and testing of ADAS features
  • Examine and diagnose the key factors driving these metrics, uncover trends, and prioritize engineering initiatives that will most improve the product experience.
  • Customize, reconfigure and rebuild processing pipelines in the software stack.
  • Integrate hardware and software components efficiently and build scalable solutions alongside our partners
  • Collaborate with our global engineering teams in our US, APAC, and Europe locations to deploy solutions to our customers.

What we need to see:
  • Well-rounded knowledge of how an autonomous vehicle stack-or any similarly complex system-functions, and real-world experience solving the challenges of bringing diverse components together into a scalable solution
  • 5+ years of work related experience in software development related to embedded systems and/or autonomous driving technologies.
  • BS/MS in computer science, robotics, electrical engineering, or related technical field (or equivalent experience).
  • Excellent C/C++ development skills with good knowledge of Python.
  • Established proficiency in system performance and complexity evaluation to optimize the system and resolve application issues.
  • Experience with automotive design processes and standards (e.g. ISO 26262 FuSa, ISO 21448 SOTIF, ASPICE), including in-vehicle testing, simulation and development guided by measurable outcomes.
  • Ability to adapt to fast paced development lifecycles and multi-functional organizations, new technologies and platforms.
  • Strong analytical skills, strive for innovative solutions, with outstanding attention to details.

Ways to stand out from the crowd:
  • Familiarity of NVIDIA DRIVE platform and NVIDIA GPU hardware and CUDA programming.
  • Software development experience on QNX or equivalent RTOS.
  • Prior experience in application development and familiarity with middleware frameworks and intricate system-level integrations.
  • Experience as ADAS software engineer at a Tier 1 or OEM
  • In-vehicle networking and application frameworks: CAN, Flexray, Ethernet, Some/IP, Classical and Adaptive AUTOSAR.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 5, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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