Senior Data Backend Engineer at NVIDIA

, Colorado, United States -

Full Time

Start Date

Immediate

Expiry Date

17 May, 26

Salary

287500.0

Posted On

16 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Golang, Kubernetes, Helm, Hive, Parquet, SQL, Vector Databases, Milvus, ETL Pipelines, Big Data Engines, Streaming, RAG Workflows, Microservices, Distributed Computing, AI Training

Industry

Computer Hardware Manufacturing

Description

NVIDIA is a global leader in high-speed computer vision, artificial intelligence (AI), and deep learning. Our team develops data engineering solutions that empower AI developers in autonomous vehicle (AV) domains to innovate quickly and effectively at scale. Are you ready to take on a senior technical role in building high-performance AI data pipelines? We seek an exceptional individual to design and optimize microservices and data pipelines to process massive volumes of AV data and enable seamless data mining and AI training. The ideal candidate will bring expertise in big data processing and distributed computing to create efficient solutions and overarching architectures for challenges such as video data curation, behavioral search, and AI dataset management. What you'll be doing: Scope and build tools, microservices, workflows, and distributed applications to accelerate data mining and AI training. Design and implement solutions for streaming, resilience, logging, security, authentication, workflow orchestration, and data management. Deploy AI models. Design and develop Retrieval-Augmented Generation (RAG) workflows enabling hybrid and agentic patterns. Analyze and operationalize complex distributed systems for speed-of-light performance. What we need to see: Master’s degree in Computer Science | Electrical Engineering (or equivalent experience). 8+ years of experience developing high-performance, scalable software systems. Strong programming skills in Python or Golang Proficiency in key technologies like Kubernetes, Helm, Hive, Parquet, SQL, vector databases, e.g., Milvus. Strong architectural skills with a proactive, problem-solving mentality. Experience in data mining | AI development Experience building ETL pipelines and working with big data engines. Exceptional collaboration skills to work with system software and AI expert teams. Eagerness to learn and adopt new technologies such as NVIDIA RAPIDS. Ways to Stand Out from the Crowd: Prior experience with large-scale real-time streaming, augmented reality, or data curation. Prior background with Spark. Exposure to the latest advances in AI, including Large Language Models, Vision-Language Models, and Retrieval-Augmented Generation (RAGs). Innovative results, including patents, publications, or open source contributions. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until February 19, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse 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. NVIDIA is the world leader in accelerated computing. NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Learn more about NVIDIA.

Responsibilities

The role involves scoping, building tools, microservices, and distributed applications to accelerate data mining and AI training for autonomous vehicle data. Responsibilities include designing solutions for streaming, resilience, security, workflow orchestration, and deploying AI models, including Retrieval-Augmented Generation (RAG) workflows.