Senior ML Data Pipeline Engineer — Equity Eligible

Nvidia Corporation in; Santa Clara (CA); On-site; USD 140,000 - 270,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is hiring a Senior Machine Learning Data Pipeline Engineer in Santa Clara, CA. You will design scalable data pipelines, build agentic workflows, and deploy production systems to support end-to-end autonomous driving foundation models.

You will collaborate with MLEs and data analysts, translate data needs into reusable mining capabilities, and help improve model data coverage through feedback and automation. Equity and comprehensive benefits accompany the role.

Qualifications

• BS or MS in Computer Science, Mathematics or Electrical Engineering, or equivalent experience.
• 5+ years in software or data engineering.
• Strong Python and SQL skills, shown through production services, APIs, or data pipelines.
• Hands-on development of data solutions and optimization including diagnosing DNN model performance.

Responsibilities

• Design, build, and own scalable data pipelines that automate data discovery, selection, and curation for DNN training data needs.
• Develop agentic workflows to identify model data needs and plan mining tasks using data tools and model inference.
• Deploy and operate pipelines as production systems with monitoring and failure recovery.
• Partner with MLEs and data analysts to turn data needs into reusable mining capabilities and improve coverage.

Skills

Python

SQL

Data pipelines

LLM/embedding concepts

Production services

Workflow automation

Education

BS in Computer Science

MS in Computer Science or Electrical Engineering

Mathematics or related field

Tools

APIs

Workflow orchestration

Job description

NVIDIA Corporation is hiring a Senior Machine Learning Data Pipeline Engineer in Santa Clara, CA. You will design scalable data pipelines, build agentic workflows, and deploy production systems to support end-to-end autonomous driving foundation models.

You will collaborate with MLEs and data analysts, translate data needs into reusable mining capabilities, and help improve model data coverage through feedback and automation. Equity and comprehensive benefits accompany the role.