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Temporary Nvidia Autonomous Driving Jobs in Colorado

Compa

Senior Software Engineer (all teams)

Denver, CO · On-site

$126K - $166K/yr

NVIDIA, Stripe, DoorDash, Open AI, TMobile, Moderna, Workday, Ulta, Target, and more. Locations ... Experience driving projects autonomously through ambiguity (scoping to delivery) * Experience ...

Prime Robotics

Senior Robotics Engineer

Denver, CO · On-site

$150K/yr

Architect and develop robotics software in ROS/ROS2 for autonomous mobile robots, from motion and ... Troubleshoot complex field and lab issues across hardware/software boundaries, driving root cause ...

Prime Robotics

Senior Robotics Engineer

Denver, CO · On-site

$150K/yr

Architect and develop robotics software in ROS/ROS2 for autonomous mobile robots, from motion and ... Troubleshoot complex field and lab issues across hardware/software boundaries, driving root cause ...

Prime Robotics

Senior Robotics Engineer

Denver, CO · On-site

$150K/yr

Architect and develop robotics software in ROS/ROS2 for autonomous mobile robots, from motion and ... Troubleshoot complex field and lab issues across hardware/software boundaries, driving root cause ...

Compa

Senior Software Engineer (all teams)

Denver, CO · On-site

$165K - $220K/yr

NVIDIA, Stripe, DoorDash, OpenAI, Moderna, Workday, Ulta, Target, and more. Come build with us! The ... Experience driving projects autonomously through ambiguity (scoping to delivery) * Experience ...

Molson Coors

RMMC Temporary Worker

Coaldale, CO · On-site

$24/hr

Responsible for autonomous maintenance of valves, motors, pumps, filter and gear boxes including ... Previous experience driving a forklift or willingness to be trained to operate a forklift

Leinenkugel's

RMMC Temporary Worker

Coaldale, CO · On-site

$24/hr

Responsible for autonomous maintenance of valves, motors, pumps, filter and gear boxes including ... Previous experience driving a forklift or willingness to be trained to operate a forklift

Unit8 SA

Deployment Strategist (USA)

Denver, CO · On-site

$125K - $161K/yr

Unit8 is dedicated to driving AI adoption in non-digital industries , accelerating their digital ... Pioneering role and autonomy: As a key member of our US growth, you will have the freedom to shape ...

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Temporary Nvidia Autonomous Driving information

What is a temporary Nvidia autonomous driving job?

Temporary Nvidia Autonomous Driving jobs are short-term positions at Nvidia focused on developing, testing, or supporting autonomous vehicle technologies. These roles may involve software engineering, data analysis, system testing, or support functions related to self-driving car platforms. Temporary roles are typically project-based, offering opportunities to work on cutting-edge artificial intelligence and robotics applications within the autonomous driving sector. Such positions provide valuable experience in the fast-evolving field of automated vehicles, even if they are not permanent.

What skills and qualifications are needed for a temporary Nvidia autonomous driving engineer?

To excel as a Temporary Nvidia Autonomous Driving Engineer, you need strong programming skills (especially in C++ and Python), a solid background in robotics or computer vision, and typically a degree in computer science, engineering, or a related field. Experience with autonomous vehicle platforms, Nvidia DRIVE, deep learning frameworks (like TensorFlow or PyTorch), and familiarity with sensor fusion technologies are highly valued. Excellent problem-solving abilities, teamwork, and adaptability are crucial soft skills for integrating new technologies and collaborating across multidisciplinary teams. These competencies ensure safe, innovative solutions in the rapidly evolving field of autonomous vehicles.

What are common challenges faced by a temporary Nvidia autonomous driving specialist, and how can applicants prepare for them?

Temporary specialists in Nvidia's Autonomous Driving division often encounter fast-paced project timelines and rapidly evolving technical requirements. Adapting quickly to new tools, frameworks, and proprietary systems is essential, as is a willingness to collaborate across multidisciplinary teams such as software engineering, data annotation, and hardware integration. Applicants can prepare by demonstrating strong foundational knowledge in machine learning, computer vision, and robotics, as well as effective communication skills to navigate a dynamic, innovative environment.

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Temporary Nvidia Autonomous Driving jobs near you
Infographic showing various Temporary Nvidia Autonomous Driving job openings in Colorado as of September 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, and 3% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Senior Deep Learning Engineer - Autonomous Vehicles

Boulder, CO • On-site

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidiaexternal

$108K - $148K/yr

Full-time

Posted 3 days ago

New

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

Job description

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. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are in search of a Senior Deep Learning Systems Engineer to propel NVIDIA's Autonomous Vehicles project forward. In this role, you will build and scale training libraries and infrastructure that make end-to-end autonomous driving models possible. By enabling training on thousands of GPUs and massive datasets, you will accelerate iteration speed and improve safety, working closely with research and platform teams across NVIDIA.

What you'll be doing:

  • Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.

  • Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.

  • Building robust training pipelines and libraries to handle massive video datasets and enable rapid experimentation.

  • Collaborating with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.

  • Owning core infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.

  • Partnering with leadership to ensure infrastructure scales with growing GPU capacity and dataset size while maintaining developer efficiency and stability.

What we need to see:

  • BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience.

  • 12+ years of professional experience building and scaling high-performance distributed systems, ideally in ML, HPC, or large-scale data infrastructure.

  • Extensive knowledge in deep learning frameworks (PyTorch is preferred), large scale training (DDP/FSDP, NCCL, tensor/pipeline parallelism), and performance profiling.

  • Strong systems background: datacenter networking (RoCE, IB), parallel filesystems (Lustre), storage systems, schedulers (Slurm, Kubernetes, etc.).

  • Proficiency in Python and C++, with experience writing production-grade libraries, orchestration layers, and automation tools.

  • Ability to work closely with multi-functional teams (ML researchers, infra engineers, product leads) and translate requirements into robust systems.

Ways to stand out from the crowd:

  • Shown experience scaling large GPU training clusters with >1,000 GPUs.

  • Contributions to open-source ML systems libraries (e.g., PyTorch, NCCL, FSDP, schedulers, storage clients).

  • Expertise in fault resilience and high availability, including elastic training and large-scale observability.

  • Tried leadership skills as a hands-on technical authority, encouraging others and establishing guidelines for ML systems engineering.

  • Familiarity with reinforcement learning (RL) at scale, particularly in the context of simulation-heavy workloads.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 12, 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.#deeplearning

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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