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Senior Software Engineer, ML Loop

On-site
NVIDIASanta Clara, CA, US / US, CA, US22 hours agoWebsite
FreshRecently launched
Full-time
Senior

Compensation

Salary undisclosed
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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.


Step into a role where you can make a significant impact on the future of autonomous vehicles. As a Senior Software Engineer, ML Loop - Automotive at NVIDIA, you will be at the forefront of our data flywheel operation. This is your opportunity to work with hardworking individuals and pioneer innovative technologies to contribute to world-class solutions.


What You’ll Be Doing:

  • Design and lead cloud and in-car data mining strategy and operations, provide strong support to corner case identification, data delivery and case resolution for perception and E2E models.
  • Leverage AI and build software technology to accelerate in-car mining speed and quality.  Work with the platform team to make sure in-car modules provide sufficient capability to support data collection needs.
  • Design and implement operational processes using data analysis, big data and software techniques to ensure data collected via collection and production vehicles are of high quality for model training.  

What We Need to See:

  • Deep understanding of AV data format and data content, including sensors and log information.  Proficient in using visualization and mining tools related to these data.
  • Understand data closed-loop methodology for improving model performance and hands-on experience with large scale data operation to practise such methodology.
  • Proficiency with modern data technology stacks, have solid foundations in statistics and machine learning fields.
  • Excellent communication skills and a collaborative, team-focused approach.
  • Bachelor’s degree in Computer Science or related field, or equivalent experience, with 8+ years in relevant industry or research roles.

Ways to Stand Out from the crowd:

  • Industry experience in autonomous driving data operations, including data collection, data mining and data delivery.
  • Industry experience practising data closed loop with production vehicles. 
  • Operational expertise in balancing cost-effectiveness, engineering quality, and time-to-market demands.
  • Demonstrated success in implementing solutions in high-stakes, ambitious environments.

Embrace this outstanding opportunity to be part of NVIDIA's ambitious journey and help craft the future of autonomous driving through outstanding data engineering.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 6, 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.

Stack

Autonomous VehiclesGPUMachine LearningData Engineering
Posted
Oct 2, 2026
Last seen
Oct 2, 2026
First seen
Oct 2, 2026

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