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Temporary Nvidia Engineering Jobs (NOW HIRING)

Bedrock Robotics

Hardware Engineer

San Francisco, CA · On-site

$145K - $192K/yr

Strong foundational knowledge in traditional HW engineering subjects such as electrical design ... High performance embedded compute, in particular Nvidia Jetson lineup * High and low speed ...

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Temporary Nvidia Engineering information

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$57K

$137K

$197K

How much do temporary nvidia engineering jobs pay per year?

As of Jul 18, 2026, the average yearly pay for temporary nvidia engineering in the United States is $137,006.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,500.00 and $151,500.00 per year, depending on experience, location, and employer.

What are Temporary Nvidia Engineering jobs?

Temporary Nvidia Engineering jobs are short-term positions at Nvidia, typically filled to meet project demands, cover employee absences, or provide specialized skills for a limited period. These roles can range from hardware and software engineering to research and development positions. Temporary engineers work on innovative projects involving graphics processing, AI, and other cutting-edge technologies. Although these jobs are not permanent, they provide valuable experience and networking opportunities within a leading tech company like Nvidia.

What are the key skills and qualifications needed to thrive as a Temporary Nvidia Engineer, and why are they important?

To thrive as a Temporary Nvidia Engineer, you need a solid background in computer engineering, programming (C/C++ or Python), and experience with hardware or software development, often supported by a relevant degree. Familiarity with Nvidia’s development tools such as CUDA, GPU architecture, and version control systems is typically required. Strong problem-solving skills, adaptability, and effective communication help you quickly integrate with teams and adapt to project needs. These skills ensure high productivity and quality contributions in a fast-paced, innovation-driven environment where contract roles demand rapid impact.

What is the difference between Temporary Nvidia Engineering vs Temporary Nvidia Data Scientist?

AspectTemporary Nvidia EngineeringTemporary Nvidia Data Scientist
Required CredentialsBachelor's or Master's in Engineering, Computer Science, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentHardware development, software engineering, system testingData analysis, model development, statistical analysis
Employer & Industry UsageUsed in hardware and software product development within NvidiaUsed in AI, machine learning projects, and data-driven solutions at Nvidia

Temporary Nvidia Engineering focuses on hardware and software development, requiring engineering credentials and working in product development environments. In contrast, Temporary Nvidia Data Scientist emphasizes data analysis and modeling skills, working primarily on AI and machine learning projects. Both roles are essential in Nvidia's innovation pipeline but differ in their technical focus and daily tasks.

What types of projects do Temporary Nvidia Engineering roles typically work on, and how do they collaborate with full-time teams?

Temporary Nvidia Engineering roles often focus on short-term, high-priority projects such as software development, hardware validation, or performance optimization. Contractors are usually integrated into existing teams and work closely with full-time engineers, project managers, and cross-functional partners to meet project milestones. While the assignments are time-bound, temporary engineers are expected to contribute actively during team meetings, participate in code reviews, and share updates regularly. This collaborative environment helps ensure project continuity and gives temporary staff valuable exposure to Nvidia’s cutting-edge technologies and workflows.
More about Temporary Nvidia Engineering jobs
What cities are hiring for Temporary Nvidia Engineering jobs? Cities with the most Temporary Nvidia Engineering job openings:
What are the most commonly searched types of Nvidia Engineering jobs? The most popular types of Nvidia Engineering jobs are:
What states have the most Temporary Nvidia Engineering jobs? States with the most job openings for Temporary Nvidia Engineering jobs include:
What job categories do people searching Temporary Nvidia Engineering jobs look for? The top searched job categories for Temporary Nvidia Engineering jobs are:
Temporary Nvidia Engineering jobs near you
Infographic showing various Temporary Nvidia Engineering job openings in the United States as of July 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $137,006 per year, or $65.9 per hour.
Autonomous Vehicle Test Engineer supporting Nvidia

Autonomous Vehicle Test Engineer supporting Nvidia

Sustainable Talent

San Francisco, CA • Remote

$70 - $97/hr

Full-time

PTO

Posted 10 days ago

Job description

Autonomous Vehicle Test Engineer

Location: Remote, United States
Employment Type: Contract / Temporary
Work Location: US, CA, Remote

Sustainable Talent is partnering with NVIDIA, a global leader that has been transforming computer graphics, PC gaming, and accelerated computing for over 25 years. We are looking for an Autonomous Vehicle Operator – Autonomous Vehicle Test Engineer to support our client's autonomous vehicle testing team. This role is remote and will focus on test creation, quality analysis, and issue investigation for autonomous vehicle software systems. This is a W-2 full-time REMOTE contract role. We offer competitive pay $70/hr-$97/hr based on factors like experience, education, location, etc. and provide full benefits, PTO, and amazing company culture!

We are seeking a highly technical and detail-oriented professional who is passionate about autonomous vehicle technology and excited to work at the intersection of software, hardware, and vehicle testing. In this role, you will analyze issues reported from vehicle testing, create and manage test suites, support testing infrastructure, and help improve the quality and accuracy of autonomous vehicle software.

What You'll Be Doing

As a member of the Autonomous Vehicle Test team, you will support end-to-end problem analysis for issues identified during daily vehicle testing. You will work closely with software and hardware engineering teams across multiple disciplines to help deliver a high-quality autonomous driving product.

Responsibilities include:

  • Analyze issues reported from routine autonomous vehicle testing.
  • Execute problem analysis processes, including issue triage, root cause analysis, issue categorization, reporting, and summary documentation.
  • Create test suites, manage test configurations, and support infrastructure for running tests.
  • Analyze test accuracy and investigate root causes of errors that lead to inaccurate test results.
  • Communicate with development teams to understand functional design and stay current on evolving technologies.
  • Develop documentation and tools to support issue analysis.
  • Collect test data from routine in-car testing and provide feedback on software performance after testing and analysis.
  • Collaborate with automotive software testing, software engineering, and hardware engineering teams to improve product quality.
What We Need to See
  • Technical education or background in Electrical Engineering, Automotive Engineering, Computer Science, Software Engineering, or a related field.
  • Experience and proficiency with Python.
  • Experience in test engineering within a robotics or automotive environment.
  • Strong analytical and problem-solving skills.
  • Ability to perform issue triage, root cause analysis, and technical documentation.
  • Self-motivated mindset with a willingness to learn new technologies and adapt in a fast-moving environment.
  • Strong communication skills and the ability to collaborate with cross-functional engineering teams.
  • Passion for autonomous vehicle technology and software quality.
Ways to Stand Out from the Crowd
  • Experience in software testing or software development for autonomous vehicles or autonomous driving systems.
  • Experience creating test suites or managing test infrastructure.
  • Familiarity with vehicle data analysis, robotics testing, or automotive software validation.
  • Ability to work across both software and hardware teams in a technical testing environment.
About Sustainable Talent

Sustainable Talent is a certified woman-owned company specializing in recruitment, consulting, and workforce solutions. We partner with innovative organizations to connect exceptional talent with meaningful opportunities across technology, engineering, operations, and professional services.

Equal Opportunity Statement

Sustainable Talent is proud to be an equal opportunity employer. We are committed to building a diverse and inclusive workforce and welcome applicants from all backgrounds, experiences, and perspectives.

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