NVIDIA is hiring a Senior Software Engineer to work on improving the data ingestion platform in our Autonomous Vehicles division! As a Data Ingestion engineer for Autonomous Vehicles Infrastructure, you will play a crucial role in managing and optimizing the flow of data from various sources into our AV systems. Your primary focus will be on ensuring the seamless ingestion and efficient serving of AV data to support critical operations.
What you'll be doing:
Implement and maintain data ingestion pipelines from diverse sources, ensuring a continuous and reliable flow of AV data into the system.
Design and optimize data serving mechanisms to deliver AV data to different teams and applications in real-time and batch processing scenarios.
Monitor data pipelines and services to proactively identify and resolve any issues, ensuring data availability and reliability.
Collaborate with cross-functional teams to improve data processing efficiency, reduce latency, and enhance overall system performance.
Implement validation and data quality checks to ensure the integrity and accuracy of ingested data.
Scale data infrastructure to handle the ever-increasing volumes of AV data generated by our expanding fleet of vehicles.
Create and maintain detailed documentation for data ingestion and serving processes, ensuring knowledge sharing across the team.
Work closely with the AV development team to understand data requirements and contribute to the enhancement of data-driven solutions.
What we need to see:
Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).
8+ years of relevant experience working on autonomous vehicles and/or software infrastructure.
Extensive expertise in developing distributed systems.
Proven experience in designing and building data ingestion pipelines for large-scale systems.
Strong proficiency in data warehousing concepts, data modeling, and database management systems.
Proficient in Go, C++ and have experience with scripting languages such as Python or Matlab in a Linux environment
Familiarity with distributed computing frameworks like Apache Spark or Hadoop.
Hands-on experience with data streaming technologies (e.g., Kafka, RabbitMQ) is a plus.
Knowledge of cloud-based platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
You will also be eligible for equity and benefits.
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.Skills Required
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience
- 8+ years of relevant experience working on autonomous vehicles and/or software infrastructure
- Extensive expertise developing distributed systems
- Experience designing and building data ingestion pipelines for large-scale systems
- Strong proficiency in data warehousing, data modeling, and database management systems
- Proficiency in Go and C++, with scripting experience in Python or Matlab, in a Linux environment
- Familiarity with distributed computing frameworks such as Apache Spark or Hadoop
- Knowledge of cloud platforms such as AWS, GCP, or Azure, and containerization with Docker or Kubernetes
- Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment
- Hands-on experience with data streaming technologies such as Kafka or RabbitMQ
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
